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Stampix
# Understanding Stampix’ users through analysis of user-generated images
## Impact | scraping/output/-7553359527278651481.txt | [
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Stampix
# Understanding Stampix’ users through analysis of user-generated images
## Impact
To support Stampix’ journey towards a 1-click photobook experience Stampix and
ML6 leveraged machine learning using AWS SageMaker. To kick off, all photos
are stored on S3 and then ingested on Sagemaker to anonymise all faces and
personal information. Afterwards, ML6 analysed Stampix’ user database,
classifying users’ interests and recommending photobooks as a collection of
their photos. This interest classification and users’ mapping onto these,
allows Stampix to address user preferences more precisely in order to optimise
marketing campaigns.
## Intro to the customer | scraping/output/-7553359527278651481.txt | [
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## Intro to the customer
Stampix is a photo printing service that has a clear mission to make people
happy through photos. The company focuses on providing a fun and user-friendly
experience, ensuring that each individual can easily navigate the process and
experience the joy of receiving their printed photos right at their doorstep.
In addition to serving individual consumers, Stampix also collaborates with
businesses to help them enhance customer satisfaction and foster loyalty. By
seamlessly integrating Stampix's photo products into their loyalty programs or
marketing initiatives, businesses are able to make their customers feel valued
and establish strong emotional connections.
## Challenge | scraping/output/-7553359527278651481.txt | [
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## Challenge
To be able to deliver increased value for both consumers and businesses, it’s
critical that Stampix understands who its users are as well as what they need,
expect, and value from its services. These insights can then be used towards
the business’ goal of creating a 1-click photobook experience to its users.
Stampix first started to collaborate with ML6 to explore how to leverage
machine learning techniques to achieve this goal.
By
## Solution
In order to propel Stampix on their journey towards a 1-click photobook
experience, ML6 and Stampix collaborated to establish guided personalised
photobook creation based on pictures that were anonymised through SageMaker.
Building this first version in co-creation with Stampix, allows them to learn
the underlying concepts and ensures they have all the tools & know-how to
continue this work. | scraping/output/-7553359527278651481.txt | [
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The approach is based on the idea that a computer can learn to recognise and
group similar pictures together, without any human help. Once it has learned
to do this, it can then bundle similar users together based on these groups of
pictures. Each of these groups of people describes a user persona. Storylines
are then associated with sets of key sentences, example images and target
dates, and are mapped to those user personas. This allows Stampix to
automatically suggest storylines that are most likely to be relevant to a
given user persona. The user can then select the storylines that they are most
interested in. They can then automatically suggest the most relevant resources
to help the user achieve each of their selected storylines. In this way,
Stampix is able to provide a 1-click photobook experience that is personalised
for each user.
This approach can be summarised in the following three steps: | scraping/output/-7553359527278651481.txt | [
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This approach can be summarised in the following three steps:
1. Creating smart groups of images by understanding the content of the images.
2. Creating smart user personas based on the image groups they interact with.
3. Compose photobooks with a storyline based on identified user personas using sets of key sentences, sets of example images, and target dates.
By
## Results
##### Creating smart groups of images
First we create smart groups of images by grouping them together based on what
content is recognized in each of the images. For this step we use pre-trained
deep learning models to extract the embeddings for each of the user’s photos. | scraping/output/-7553359527278651481.txt | [
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Next, we annotate the image clusters by embedding popular image captions taken
from an existing large dataset containing millions of image captions to the
same embedding space as the anonymised image embeddings. We can then calculate
the closest caption embedding to each of the clusters’ centres which results
in a set of predicted captions for each image cluster.
##### Creating smart user personas
To create user personas, we analyse users' interactions with the image
clusters, grouping similar users together based on their preferences and
interests, and identifying the dominant topics of each user persona by looking
at the captions associated with the image clusters. More specifically, we
create user embeddings based on each user’s interactions with the image
clusters. These user embeddings are then once again clustered to group similar
users together to form personas.
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These clusters can then identify the personas by looking at how much each
image cluster attributes to the average user embedding of each cluster. This
way the most dominant topics of each user persona can be identified by the
textual content of the captions associated with the image clusters most
contributing to that user persona.
##### Composing photobooks using storylines
By understanding the personas of their users, Stampix can make more informed
decisions about which storylines and resources to suggest to each user. For
example, a user persona that is interested in travel and nature photography
may be more likely to be interested in a photobook with a storyline about a
nature hike or a trip to a national park. On the other hand, a user persona
that is interested in family and children photography may be more likely to be
interested in a photobook with a storyline about a family reunion.
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These insights can then be used to generate photobooks using sets of key
sentences, sets of example images and target dates describing a storyline
aligned with the detected photobook personas.
This approach allows Stampix not only to automatically generate personalised
photobooks for each user without the need for a human editor, but also to
understand the interests and preferences of their users on a much more
foundational level. This improves the user experience, generates more value
for their customers and serves as a groundwork for many future iterations.
We would like to thank Stampix for the opportunity to work with them on this
project. ML6 will continue to provide expert support where needed.
Accelerating businesses with AI technology & experts
Contact:
info@ml6.eu
+32 9 265 95 50
Contact us
Join our newsletter
By subscribing you agree to with our Privacy Policy
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Machine learning engineerDelivery unit 👩💻 \- Office Amsterdam 📍 | scraping/output/-8920162832192305058.txt | [
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Senior ML engineerDelivery unit 👩💻 \- Office Berlin 📍
Senior ML engineerDelivery unit 👩💻 \- Office Ghent 📍
Machine learning engineerDelivery unit 👩💻 \- Office Amsterdam 📍
Project ManagerDelivery unit 👩💻 \- Office Ghent 📍
Project ManagerDelivery unit 👩💻 \- Office Berlin 📍
Machine learning engineerDelivery unit 👩💻 \- Office Berlin 📍
Machine learning engineerDelivery unit 👩💻 \- Office Ghent 📍
Data engineerDelivery unit 👩💻 \- Office Ghent 📍
Customer engineerLabs unit 🧪 \- Office Ghent 📍
InternshipOffice Amsterdam 📍, Office Berlin 📍, Office Ghent 📍
Spontaneous applicationOffice Amsterdam 📍, Office Berlin 📍, Office Ghent 📍
## Destination: dream job
Your mission as an ML6 agent? Empowering businesses with state-of-the-art AI
technology. | scraping/output/-8920162832192305058.txt | [
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Spontaneous applicationOffice Amsterdam 📍, Office Berlin 📍, Office Ghent 📍
## Destination: dream job
Your mission as an ML6 agent? Empowering businesses with state-of-the-art AI
technology.
We are a team of ambitious and enthusiastic AI experts dedicated to help you
grow your talent. During our recruitment process, we take the time to get to
know you and match you with the right role. Apply today and reach your full
potential at ML6!
Jobs
Our DNA
1
Get to know each other
Starting your ML6 journey means connecting with one of our recruiters who will
guide you as they get to know you.
2
Technical matching
We work with you to match your skills and interests with our projects, setting
you up for success in your role at ML6.
3
Presentation time
Time to show our team how you can contribute to our innovative projects by
demonstrating your skills & creativity.
4
Final meeting | scraping/output/-8920162832192305058.txt | [
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] |
3
Presentation time
Time to show our team how you can contribute to our innovative projects by
demonstrating your skills & creativity.
4
Final meeting
As you approach the finish line, we’ll have a final chat to reflect on your
candidate journey and your dream job at ML6.
#### What our ML6 agents have to say
" After 3 months internship at ML6, where I discovered the wonderful world of
AI, I got the opportunity to join the team officially as a Customer Engineer
where I help translating business needs into technical solutions. "
Pauline Nissen
Customer Engineer
" As a Sales Consultant I frequently go to production environments of
customers to learn more about how they work, but also identify challenges that
they are facing. My role is very diverse. I'm responsible for full sales
cycles. This includes new business, account management and partnerships. "
Stan Callewaert
Sales Consultant
Hi, I’m Julie
Talent Partner | scraping/output/-8920162832192305058.txt | [
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AI solutions | scraping/output/-1012769412128074250.txt | [
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# Senior Machine Learning Engineer
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## Your challenge | scraping/output/505228400486366403.txt | [
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Join us
## Your challenge
Are you on the look to create real impact in the world of AI? Exciting
developments are happening, offering opportunities for businesses to innovate
and gain a competitive edge. Now is the time to join us and leverage those
AI/ML skills to a next level while working on the most innovative projects for
the biggest clients across Europe such as Randstad, ASML, FUNKE, and many
more! Whether it’s about leveraging LLMs to improve customer support, building
data lakes on cloud platforms to improve storage or implementing sensors for
quality control. You can find it all at ML6.
If you consider yourself a machine learning expert who can not only develop
and validate performant models, but also has what it takes to take these
models all the way to a deployment to thousands or millions of users, ML6 can
provide you with a number of challenging use cases to sink your teeth into. | scraping/output/505228400486366403.txt | [
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You will mostly work with Python to solve varied Machine Learning tasks, using
various frameworks such as Tensorflow, Pytorch, or HuggingFace and to help put
these applications into production on the cloud in order to generate business
value for our clients. You make applications that are carefully architected,
scalable and robust through your combined skills in engineering and machine
learning.
ML6 delivers projects on all major cloud providers (GCP, AWS, Azure).
As a senior, you take up the tech lead role on a per-project basis, and lead
your more junior colleagues in both the technical and client-facing aspects of
a project. Internally, you take a leading role in driving forward the
company’s technical capabilities and client offerings.
## Briefly explained, you: | scraping/output/505228400486366403.txt | [
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## Briefly explained, you:
* Are a born consultant that understand customer business needs and translate them into end-to-end technical solutions
* Use Python to deploy production ready pipelines and ML models on the Cloud
* Explore state-of-the art ML research and drive internal evaluation and adoption of cutting edge tools and frameworks
* Are responsible for the high-quality delivery of your team’s projects
* Technically guide junior ML engineers
* Deliver technical workshops for clients
* Leverage your expertise to help sales qualify and land exciting projects
## Who are you? | scraping/output/505228400486366403.txt | [
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## Who are you?
* Excellent written and verbal communication skills in English (Dutch/German are a plus)
* Work experience in software development
* 3+ years of work experience with Machine Learning
* Proficient in Python & software development best practices
* Degree in computer science or related field
* A coaching & knowledge sharing mindset
* Ability to provide expert advice to non-technical staff and clients
* Experience with deploying ML models to a large user base
* Worked on one of the major Cloud providers (AWS, Azure, GCP)
Considered as a plus:
* Familiarity with MLOps way of working
* Took a leading technical role in a team structure
* Experience in one of our focus domains: GenAI NLP, Vision, Bio, Ops, Energy or Digital Twins
## Why ML6? | scraping/output/505228400486366403.txt | [
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## Why ML6?
Looking for a dynamic environment where you can create real business impact
with AI? Look no further. Don’t expect a big corporate organisation with pre-
defined jobroles and plans for the coming years. Expect the unexpected.
Growth, change and impact. Expect to work for the most innovative and biggest
companies across countries. Expect exponential personal growth in your career.
We provide an attractive salary package for your expertise and an optimised
benefits program where we stay true to our caring and learning goals. In a
nutshell, we've built a place where we truly love working, we think you will
too.
Scroll down to find out more about why others choose ML6! 👇
Department
Advisory & Delivery unit 💻
Locations
Office Ghent 📍, Office Amsterdam 📍, Office Berlin 📍
Employment type
Full-time
## Why others choose ML6 🤝
* ### Create intelligence with a lasting positive impact | scraping/output/505228400486366403.txt | [
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Office Ghent 📍, Office Amsterdam 📍, Office Berlin 📍
Employment type
Full-time
## Why others choose ML6 🤝
* ### Create intelligence with a lasting positive impact
As a leader in AI, we work hard to ensure that AI is designed, developed and
deployed to create positive impact. We take our responsibility to build secure
and sustainable technology seriously and have integrated ethics within our way
of working. This shows in every client case and do good projects we do.
* ### Innovate and share knowledge
Learning is part of our DNA. Whether it's through our team's expertise,
creating spin-offs or the latest tech breakthrough, our culture will empower
you to deliver top-notch AI solutions to our customers. We organise chapter
conferences, guest lectures, meet ups, dedicate time to research, blogposts, a
personal training catalog and so much more.
* ### We achieve more together | scraping/output/505228400486366403.txt | [
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* ### We achieve more together
Expect to build lasting relationships that extend beyond the office walls.
Thanks to our collaborative and diverse culture, we achieve the extraordinary.
From our ML6 agents to our ML6 Maffia, we’ve created a safe environment where
mutual trust and open feedback is cherished. To foster our interpersonal
connections, we love to see each other's pretty faces at the office.
* ### Fast growing and international
We're gearing up for our next growth milestone. Don’t expect a big corporate
organisation with pre-defined jobroles and plans for the coming years. Expect
the unexpected. Growth, change and impact. Expect to work for the most
innovative and biggest companies across countries. Expect exponential personal
growth in your career.
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* ### Byte size Benefits
Last but not least, we provide an attractive salary package for your expertise
and an optimised benefits program where we stay true to our caring and
learning goals. In a nutshell, we've built a place where we truly love
working, we think you will too.
📽️ Working as an ML Engineer
00:00
% buffered
## FAQ
* ### Can I work remotely at ML6?
There is a reason why we don’t work (fully) remotely at ML6 and why we love
being present at our offices so often. At ML6, our culture is based on
interpersonal connections and our strength lies in our personal collaboration.
With our clients, and with each other. We work from home about 2 days a week.
Our offices are situated in Berlin, Amsterdam and Ghent.
* ### What to expect when joining ML6? | scraping/output/505228400486366403.txt | [
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* ### What to expect when joining ML6?
Don’t expect a big corporate organisation with pre-defined jobroles and a
defined plan for the coming years. Expect the unexpected. Growth, change and
impact. Learn from engaged experts with a like minded passion for technology.
Expect to work for the most innovative and biggest companies across countries.
We are all T-shaped consultants working on a shared goal.
* ### Am I a fit for the company?
We are an AI Consulting company on a mission. Guiding the AI revolution
towards positive impact. You can become part of this mission. We are always on
the look for business minded people with a consultative approach. We dedicate
great effort in building a caring culture full of learning opportunities that
accelerates us to accomplish our main purpose. You can be in the driver’s seat
of your career. You can be the next ML6 agent to create value for our
customers and company.
Are you up for the challenge? | scraping/output/505228400486366403.txt | [
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Are you up for the challenge?
* ### What does the application process look like?
It depends on the role that you're applying for. For our technical roles, we
always start with a technical matching (ex. coding challenge) and get to know
interview. Every role at ML6 receives a presentation challenge where we will
evaluate how you can contribute to our innovative projects by demonstrating
your skills & creativity. As you approach the finish line, we schedule a final
interview (physically) to reflect on your dream job at ML6.
* ### How is ML6 structured?
We work in Units and with Unit Coaches. For more information about our
structure, we recommend you to watch this video.
* ### What are examples of projects that ML6 worked on? | scraping/output/505228400486366403.txt | [
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We work in Units and with Unit Coaches. For more information about our
structure, we recommend you to watch this video.
* ### What are examples of projects that ML6 worked on?
At ML6, we boost and increase revenue growth for other companies, by
implementing AI solutions. We do this for a broad range of industries. From
manufacturing, to healthcare or media and entertainment industries (and lots
more!).
You can find some of our client cases and testimonials here.
* ### I would love to meet up with someone from ML6
You can find all of our upcoming meet ups and events here. If you would like
to schedule a first get-to-know, we recommend you to apply officially via our
jobsite where we will follow up with you soon.
* ### What about the ethical aspect of AI?
At ML6 we take our responsibility to build secure, reliable and sustainable
technology seriously and integrate ethics within our way of working. We have
our own Ethical Advisory board to discuss sensitive projects. | scraping/output/505228400486366403.txt | [
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* ### Why is ML6 called ML6?
ML stands for our main expertise, Machine Learning. Next to that, we don't
take ourselves always very seriously. Our people are 'ML6 agents', wink to
MI6. Seen the James Bond movies? Our meeting rooms for example are named after
them. After all, we can be a bit geeky at times ;-)
* ### What does a typical AI project look like?
This really depends on the scope of the project. A project can run for a
couple of months, to even years. Our ML6ies work on projects together with a
team of colleagues. This team can have different skills like data engineering,
software, machine learning and project management to deliver top notch service
to our clients. They sometimes work on different projects simultaneously or
combine project work with an internal project or research topic.
Contact Julie Plusquin Talent Partner – Talent & Culture 🫶
## Colleagues
Jens Bontinck
Head Advisory & Delivery
## Join us
* Frontend Engineer | scraping/output/505228400486366403.txt | [
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## About ML6 | scraping/output/505228400486366403.txt | [
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] |
* Data Engineering Consultant
Advisory & Delivery unit 💻 * Multiple locations
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Office Ghent 📍 Office Amsterdam 📍 Office Berlin 📍
## About ML6
We guide the AI revolution towards positive impact. 🌐
Exciting developments are happening in the world of AI, offering unprecedented
opportunities for businesses to innovate and gain a competitive edge. Now more
than ever is the time to create intelligence with lasting positive impact. And
you can be a part of this!
1. We deliver end-to-end projects where we accompany organisations through the entire AI journey
2. We build bespoke hybrid ML solutions
3. We navigate and set up advisory projects
As ML6 highly values diversity, inclusion and transparent communication, we've
implemented a formal channel to report serious misconduct here.
Examples of serious misconduct (not limited to): safety of the individual
(aggression, discrimination, sexual harassment), data privacy issues, public
health, tax and fraud. | scraping/output/505228400486366403.txt | [
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Examples of serious misconduct (not limited to): safety of the individual
(aggression, discrimination, sexual harassment), data privacy issues, public
health, tax and fraud.
Join us
Advisory & Delivery unit 💻 * Multiple locations
# Senior Machine Learning Engineer
## As a Senior ML Engineer, you take up the tech lead role on a per-project
basis, and lead your more junior colleagues in both the technical and client-
facing aspects of a project! 🤖
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Applicant tracking system by Teamtailor | scraping/output/505228400486366403.txt | [
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] |
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# Visualizing our tech
## Video
View all
case studies
Peter De Jaeger, Chief Innovation Officer, talking about their AI use case &
working with ML6
2:36
case studies
Shanna Cloet, IT Manager at Fost Plus, talking about their AI use case &
working with ML6.
2:53
case studies
Philippe Meire, Founder of March, talking about their AI use case & working
with ML6.
2:46
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] |
2:53
case studies
Philippe Meire, Founder of March, talking about their AI use case & working
with ML6.
2:46
case studies
Heiko Weigelt, CIO at Funke Mediengruppe, talking about their AI use case &
working with ML6.
3:43
case studies
Otary x ML6 : Optimising the production of off-shore wind farms
3min25sec
talks
What is MLOps and why should you care ?
1 min
## Demo
View all
tag
Wim De Vilder speaking Moroccan through faceswap (with VRT)
View more
tag
Multivariate Time Series Similarity
This demo is a result of research conducted in the field of multivariate time
series similarities. The goal was to develop a fast and scalable system, able
to unsupervisedly find the 5 most similar datapoints for a given reference.
View more
tag
MLSox, our April Fool's sock-matching app
View more
tag
Notebook on TensorFlow Data Validation
View more
tag
Jeroom dancing through pose transfer (with VT4/GoPlay)
View more
tag
How to spot a deepfake?
View more | scraping/output/1491972639986085933.txt | [
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] |
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] |
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customers, and therefore we are looking for someone to further strengthen and
build out the collaboration between Azure and ML6 to better serve our
customers. | scraping/output/-1407133460167179809.txt | [
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] |
You will be the “go to” person for creating, building and maintaining our
relationship with Azure and all stakeholders. Do you love taking up a large
amount of responsibility and participating in growing our business? You are
the one we’re looking for!
# Your Challenge | scraping/output/-1407133460167179809.txt | [
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* Match ML6 and Azure strategies to define overlap and create win-win initiatives
* Be responsible for building and realising our Azure partner business plans
* Be the point of contact for all ML6 related matters towards the entire Azure organisation
* Nurture a tight partnership with Azure and be the internal contact person for all Azure related news
* Make ML6 a Top of Mind Partner for all AI related projects and workloads by creating visibility and relevance for ML6 through partner programs, specialisations and certifications
* Work together with Marketing to initiate, organise and participate to different events to strengthen our collaboration with Azure and join partner organised events as well
* Gather, publish and share success stories from our collaboration with Azure
* Be involved in the launch of new products and be on top of latest innovations
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* Be involved in the launch of new products and be on top of latest innovations
* Enable specific partnership opportunities and projects with Azure
* Work closely with our Client Executives and Partners to discuss potential leads
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## Why you?
* Have at least 3 years of professional experience in a technology related field
* Experience with the work method of major cloud providers (Azure), how they work and are structured
* Are fluent in English (optional Dutch/German)
* Build true relationships easily and love to expand your network
* Work structured, clear and handle project coordination well
* Are eager to learn about AI and be on top of the latest cloud technologies
* Love variation and a diversity in tasks as no day will be the same
* Take ownership to create your own role and have a great sense of responsibility
* Have a flexible mindset as you will travel and meet a lot of new people
* Like an organised way of working and take initiative in organising things yourself
## Why ML6? | scraping/output/-1407133460167179809.txt | [
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## Why ML6?
Looking for a dynamic environment where you can create real business impact
with AI? Look no further. Don’t expect a big corporate organisation with pre-
defined jobroles and plans for the coming years. Expect the unexpected.
Growth, change and impact. Expect to work for the most innovative and biggest
companies across countries. Expect exponential personal growth in your career.
We provide an attractive salary package for your expertise and an optimised
benefits program where we stay true to our caring and learning goals. In a
nutshell, we've built a place where we truly love working, we think you will
too.
Scroll down to find out more about why others choose ML6! 👇
Department
Business Development unit 🤝
Locations
Office Amsterdam 📍, Office Berlin 📍, Office Ghent 📍
## Why others choose ML6 🤝
* ### Create intelligence with a lasting positive impact | scraping/output/-1407133460167179809.txt | [
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Business Development unit 🤝
Locations
Office Amsterdam 📍, Office Berlin 📍, Office Ghent 📍
## Why others choose ML6 🤝
* ### Create intelligence with a lasting positive impact
As a leader in AI, we work hard to ensure that AI is designed, developed and
deployed to create positive impact. We take our responsibility to build secure
and sustainable technology seriously and have integrated ethics within our way
of working. This shows in every client case and do good projects we do.
* ### Innovate and share knowledge
Learning is part of our DNA. Whether it's through our team's expertise,
creating spin-offs or the latest tech breakthrough, our culture will empower
you to deliver top-notch AI solutions to our customers. We organise chapter
conferences, guest lectures, meet ups, dedicate time to research, blogposts, a
personal training catalog and so much more.
* ### We achieve more together | scraping/output/-1407133460167179809.txt | [
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* ### We achieve more together
Expect to build lasting relationships that extend beyond the office walls.
Thanks to our collaborative and diverse culture, we achieve the extraordinary.
From our ML6 agents to our ML6 Maffia, we’ve created a safe environment where
mutual trust and open feedback is cherished. To foster our interpersonal
connections, we love to see each other's pretty faces at the office.
* ### Fast growing and international
We're gearing up for our next growth milestone. Don’t expect a big corporate
organisation with pre-defined jobroles and plans for the coming years. Expect
the unexpected. Growth, change and impact. Expect to work for the most
innovative and biggest companies across countries. Expect exponential personal
growth in your career.
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* ### Byte size Benefits
Last but not least, we provide an attractive salary package for your expertise
and an optimised benefits program where we stay true to our caring and
learning goals. In a nutshell, we've built a place where we truly love
working, we think you will too.
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* ### Can I work remotely at ML6?
There is a reason why we don’t work (fully) remotely at ML6 and why we love
being present at our offices so often. At ML6, our culture is based on
interpersonal connections and our strength lies in our personal collaboration.
With our clients, and with each other. We work from home about 2 days a week.
Our offices are situated in Berlin, Amsterdam and Ghent. | scraping/output/-1407133460167179809.txt | [
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* ### What to expect when joining ML6?
Don’t expect a big corporate organisation with pre-defined jobroles and a
defined plan for the coming years. Expect the unexpected. Growth, change and
impact. Learn from engaged experts with a like minded passion for technology.
Expect to work for the most innovative and biggest companies across countries.
We are all T-shaped consultants working on a shared goal.
* ### Am I a fit for the company?
We are an AI Consulting company on a mission. Guiding the AI revolution
towards positive impact. You can become part of this mission. We are always on
the look for business minded people with a consultative approach. We dedicate
great effort in building a caring culture full of learning opportunities that
accelerates us to accomplish our main purpose. You can be in the driver’s seat
of your career. You can be the next ML6 agent to create value for our
customers and company.
Are you up for the challenge? | scraping/output/-1407133460167179809.txt | [
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Are you up for the challenge?
* ### What does the application process look like?
It depends on the role that you're applying for. For our technical roles, we
always start with a technical matching (ex. coding challenge) and get to know
interview. Every role at ML6 receives a presentation challenge where we will
evaluate how you can contribute to our innovative projects by demonstrating
your skills & creativity. As you approach the finish line, we schedule a final
interview (physically) to reflect on your dream job at ML6.
* ### How is ML6 structured?
We work in Units and with Unit Coaches. For more information about our
structure, we recommend you to watch this video.
* ### What are examples of projects that ML6 worked on? | scraping/output/-1407133460167179809.txt | [
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] |
We work in Units and with Unit Coaches. For more information about our
structure, we recommend you to watch this video.
* ### What are examples of projects that ML6 worked on?
At ML6, we boost and increase revenue growth for other companies, by
implementing AI solutions. We do this for a broad range of industries. From
manufacturing, to healthcare or media and entertainment industries (and lots
more!).
You can find some of our client cases and testimonials here.
* ### I would love to meet up with someone from ML6
You can find all of our upcoming meet ups and events here. If you would like
to schedule a first get-to-know, we recommend you to apply officially via our
jobsite where we will follow up with you soon.
* ### What about the ethical aspect of AI?
At ML6 we take our responsibility to build secure, reliable and sustainable
technology seriously and integrate ethics within our way of working. We have
our own Ethical Advisory board to discuss sensitive projects. | scraping/output/-1407133460167179809.txt | [
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* ### Why is ML6 called ML6?
ML stands for our main expertise, Machine Learning. Next to that, we don't
take ourselves always very seriously. Our people are 'ML6 agents', wink to
MI6. Seen the James Bond movies? Our meeting rooms for example are named after
them. After all, we can be a bit geeky at times ;-)
* ### What does a typical AI project look like?
This really depends on the scope of the project. A project can run for a
couple of months, to even years. Our ML6ies work on projects together with a
team of colleagues. This team can have different skills like data engineering,
software, machine learning and project management to deliver top notch service
to our clients. They sometimes work on different projects simultaneously or
combine project work with an internal project or research topic.
Office Amsterdam 📍 Office Berlin 📍 Office Ghent 📍
## About ML6 | scraping/output/-1407133460167179809.txt | [
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# Alliance Manager - Azure | scraping/output/-1407133460167179809.txt | [
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] |
Before taking up his current role, Robbe led our delivery team for 2,5 years,
which gives him deep knowledge of how ML6 works and a wide overview of our
projects. This also helped build his people skills, which he now combines with
his technical expertise to build engineering cultures at our clients.
Robbe loves to share his knowledge by engaging with the community. He
maintains our open source API framework Connexion and our open source
foundation model finetuning framework Fondant, and contributes to the wider
open source ecosystem with some prominent contributions to Apache Beam. He has
also been featured as a speaker at meetups and conferences across Europe.
Visit my LinkedIn profile
Our know-how
## Related posts
Placeholder tag
Webinar | The future of procurement & smart document processing
Learn how intelligent technology can optimize procurement processes with
insights from Iron Mountain, Google Cloud, and ML6.
April 21, 2021
By
Robbe Sneyders
Placeholder tag | scraping/output/-5589486511817883860.txt | [
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] |
Learn how intelligent technology can optimize procurement processes with
insights from Iron Mountain, Google Cloud, and ML6.
April 21, 2021
By
Robbe Sneyders
Placeholder tag
Opinion — How to build a data architecture to drive innovation — today and
tomorrow
Building Future-Proof Data Architecture: Key Insights and Recommendations
February 11, 2021
By
Robbe Sneyders
Placeholder tag
Organizing your team for innovation
A short while ago, we were happy to receive the news that ML6 won the 2020 ‘AI
Innovator of the Year’ award in the prestigious Data News Awards for
Excellence. To celebrate our award, we would like to share some behind the
scene on how we foster innovation at ML6.
December 1, 2020
By
Robbe Sneyders
Placeholder tag
Designing better Python interfaces with keyword-only arguments
Improving Python Interfaces with Keyword-Only Arguments
December 16, 2020
By
Robbe Sneyders
Large Language Model
Foundation Models
Corporate
People
Structured Data
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Improving Python Interfaces with Keyword-Only Arguments
December 16, 2020
By
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Mission How we workResponsible AICareers | scraping/output/-5589486511817883860.txt | [
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Copyright 2024
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July 20, 2023
# AI can play a crucial role in the field of HR, but should we blindly follow?
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Julie Plusquin
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Is AI only applicable within factories and large corporate organizations?
Anything but. AI will (and already is) creating impact within the Human
Resources branch as well. We speak with Julie Plusquin, Talent Partner at ML6
about what the evolution within HR may look like.
Julie: "I have a Master's degree in Psychology. I could have asked myself the
question, 'Why continue to study about the individual, when soon algorithms
will be able to read people anyway?' Well, in this article I would like to
take you through my train of thought."
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#### Some applications of AI in HR
The future of AI in the field of Human Resources looks bright, in my opinion.
Of course, I don't want to be naive and I also mention certain risks involved.
Some concrete applications of AI within the HR field include: CV screening by
an algorithm, mapping skills of your employees and getting certain advice from
the algorithm, real-time feedback tools, and so on.
HR Analytics have also been on the rise in recent years. Companies are more
often seeing the added value of a data-driven approach. As a psychologist with
a strong background in evidence-based management, I love witnessing this
evolution. Don't make the mistake of assuming that data and people cannot be
connected. You can collect, analyze and optimize a lot of data when it comes
to performance, skills, attitude, recruitment and so on. This can help an HR
professional to make better future decisions. | scraping/output/-1024774239291424425.txt | [
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How can these applications be useful? Use them for efficiency purposes. People
today spend a lot of time on operational tasks. For example, a lot of my time
is spent screening resumes, scheduling interviews and giving feedback to
candidates. Some of these tasks can easily be automated. An important remark
here is, "Where is your added value as a person and what are the risks
associated with automating these?". | scraping/output/-1024774239291424425.txt | [
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Screening a resume, for example: An algorithm will most likely be able to
filter relevant education and the person's location faster than I can. But can
an algorithm as well as a person nuance in this? Can it understand why someone
has a 2-year gap in their CV, for example? Anyway, I prefer to engage with
people to include this personal nuance. And I think that is irreplaceable. How
is an algorithm going to measure whether someone is a cultural fit for the
organization? You can certainly set up some pre-defined questions for this,
but still don't underestimate the impact of your observations during a face-
to-face interview and how someone behaves during a tour at the office. Either
way, I think there will come a time when resumes will no longer be common when
applying for jobs. I think the recruitment world will undergo a huge turn and
(digital) development in the coming years. Thankfully.
#### Ethical AI | scraping/output/-1024774239291424425.txt | [
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#### Ethical AI
When does an AI model meet certain requirements to be able and allowed to be
deployed in day-to-day use? Are there certain guidelines for that? Within the
domain of Ethical AI and as well as our general legislation in the EU around
the application of AI, certain guidelines are written and some are still being
developed. This can mean, for example, that if AI causes harm to physical or
mental wellbeing of humans, it cannot be used. Also, there are many
discussions around the use of personal data and discrimination. As technology
is moving forward at an ever increasing speed, regulators in this domain are
also moving forward to make evolutions of the proposed regulations (EU AI
Act). | scraping/output/-1024774239291424425.txt | [
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Another important aspect is that of explainability. When an algorithm makes a
prediction, it is important to know how the decision is made. For example:
personal feedback is important to a candidate (why were you selected to go to
the next round or not). And also because we must be able to measure if there
is bias in it. For example, if a particular job is more commonly done by men,
there might be a bias in your model against women in it.
Because HR professionals focus a lot on personal contacts, we often come into
contact with sensitive data. For that very reason, we need to be critical and
careful when using AI. Is there some risk that your model would discriminate
against a candidate? Then this does not seem to be the ideal solution. | scraping/output/-1024774239291424425.txt | [
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] |
On the other hand, AI can also add value to counter human biases since they
rely purely on the available data and not on gut feeling. But make no mistake,
AI can discriminate based on limited or historical data as well. For example,
if an algorithm has more data to rely on from the past of "white" people, it
may view this data as the "norm," discriminating more quickly with data that
differs from this.
#### Resistance to Change
As an organization that daily works on AI and ML projects, we also get the
question from customers, "How can I start implementing AI within my
organization, and how do I deal with resistance to this solution from my
employees?". This concept we call "resistance to change" covers a very large
domain within the literature on Change Management within organizations. | scraping/output/-1024774239291424425.txt | [
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AI will continue to develop anyway, as well as in the domain of HR, and how we
deal with it will largely depend on the communication and guidance of coaches
in organizations. You can communicate a message in different ways. "We are
experimenting with AI to let you become more efficient in your job and
evaluate in which aspects you still want to grow." or "We are experimenting
with AI to make our company more profitable and efficient.". You immediately
notice the difference.
In addition, implementing AI in your organization offers tremendous
opportunities. By talking to your employees individually, you can identify
what someone is good at and where they still wish to grow. By having an
operational part optimized through AI, this again brings a lot of space and
opportunities to discover and learn new things. Therefore employee
satisfaction and productivity will increase. | scraping/output/-1024774239291424425.txt | [
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I can already hear the question coming, "But what if I perform 100%
operational work today?". My answer will remain the same. I believe that AI
can add value. Keep in mind that AI will replace tasks, not necessarily jobs.
I strongly believe that it will also create new jobs or make the current ones
more inspirational. New needs will create new labour. Plasticity and the
ability to adapt will therefore be the skill needed to deal with what the
future brings. In fact, this has always been the case. Have a look at Darwin's
theory of "survival of the fittest”.
#### People versus the algorithm
The power of people versus an algorithm? The difference lies in our ability to
think forward and backward. People are unique in their ability to fantasize
and imagine situations and how to deal with them. This requires creativity,
empathy and personal nuance. | scraping/output/-1024774239291424425.txt | [
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When AI applications are implemented, it still remains important to
incorporate a "human factor" into the process as control/check. Like humans,
an algorithm also needs time to learn.
Within Human Resources, I think AI can take over much of operational work. On
the other hand, I think it is important that the 'interpretation part' remains
with us as experts. Our process of evaluating performance for example could be
optimized through AI, but the interpretation of why someone has just started
performing better compared to a previous period remains up to us. In my
opinion, AI could just highlight the unique ability of humans even more. And
isn't that the perfect example of how Human Resources could go hand in hand
with AI?
> At ML6, we are a high-tech AI company. But precisely because of our human
> approach in Human Resources, we give a clear message to our people on the
> one hand, and to the outside world on the other.
## Related posts
View all
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# MLOps
Simplify ML model deployment and maintenance in production
Learn moreContact us | scraping/output/-1256552881048572912.txt | [
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# MLOps
Simplify ML model deployment and maintenance in production
Learn moreContact us
Gartner reports that only 54% of AI pilot projects make it to production, with
the rest failing to deliver business value. The answer to this issue? MLOps
(Machine Learning Operations).
MLOps applies DevOps concepts such as automation, version control, and so on
to machine learning models, making them easier to deploy, maintain and
optimize in production.
## Client cases
Discover how our expertise in Computer vision leads businesses to success
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Accelerating Innovation in the Digital Insurance Sector for Policy Expert with
AWS
Policy Expert pushed innovation in digital insurance with AWS, leveraging AI &
ML for customer insights and real-time quotes.
July 25, 2023
By
This is some text inside of a div block.
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July 25, 2023
By
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Financial services
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Placeholder tag
A smart and data driven solution for the road lighting on Flemish highways | scraping/output/-1256552881048572912.txt | [
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"Lights on highways are turned off when possible and the highways are
illuminated when necessary." Based on this lighting vision of the Flemish
government, the Agency for Roads & Traffic (AWV) is working with AI specialist
ML6 to automatically control motorway lighting based on artificial
intelligence. It will soon be possible to control highway lighting for
shorter periods and smaller regions. This will have beneficial economic,
environmental and social effects. The solution saves energy and light
pollution is countered when the lights do not have to be switched on (or can
be dimmed). Where it is required for safety, the lights are switched on. The
operator can make a data-driven decision, as a first step towards a full-
automatic control of lighting on the Flemish road network. This results in
energy savings and a reduction of light pollution, which are key objectives of
the project, are key objectives of the project, without compromising safety
for road users.
February 13, 2023 | scraping/output/-1256552881048572912.txt | [
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] |
February 13, 2023
By
Jens Bontinck
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Public & Professional Services
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Placeholder tag
Enabling MLOps to shorten GfK’s development cycle
ML6 advised and supported GfK on setting up an MLOps way-of-working, enabling
GFK to bring insights to production in weeks instead of months, at much lower
costs.
September 7, 2022
By
Robbe Sneyders
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Media & Entertainment
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Large Language Model
Foundation Models
Corporate
People
Structured Data
Chat GPT
Sustainability
Voice & Sound
Front-End Development
Data Protection & Security
Responsible/ Ethical AI
Infrastructure
Hardware & sensors
MLOps
Generative AI
Natural language processing
Computer vision
## Typical challenges
How MLOps can help your organisation overcome bottlenecks that occur during
the lifecycle of a machine learning project? Here are some examples: | scraping/output/-1256552881048572912.txt | [
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] |
Computer vision
## Typical challenges
How MLOps can help your organisation overcome bottlenecks that occur during
the lifecycle of a machine learning project? Here are some examples:
### Collaboration & communciation issues
ML development involves many teams with different needs, which can cause
collaboration problems. MLOps solves this by supporting close collaboration
and communication so that everyone - data scientists, ML engineers, software
engineers and business stakeholders - is on the same page from the beginning
of the project and knows their responsibilities.
### Poor data quality
Consistent data quality is essential for accurate ML model predictions, but
poor data quality is a common issue that ML engineers face. MLOps solves this
problem through automated data quality checks and version control tools to
track data throughout the ML model lifecycle. By identifying data issues early
on, you can avoid unexpected failures and save time in the long run. | scraping/output/-1256552881048572912.txt | [
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### Difficulties to scale and maintain
Scalable ML apps generate more business value. Why? Because they can handle
increased workload or traffic without reduced performance. MLOps improves
scalability by using automated pipelines for ML model training, evaluation,
and deployment through CI/CD processes.
## High level outline of the solution
ML applications are complex, with many different components that require
specific best practices to guarantee success.
However, while attention to individual components is crucial, there are
general best practices that all components can benefit from and that we would
like to share with you.
Modularize code into logical ML related steps
Break down an ML pipeline into smaller, manageable components such as data
ingestion and data validation. This leads to easier maintenance, updates and
reuse. Moreover, team members can work together on different components
uninterrupted.
Containerize code after experimentation phase | scraping/output/-1256552881048572912.txt | [
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Containerize code after experimentation phase
Package the code and dependencies into a container once the experimentation
phase is complete. This makes it easier to use the ML model in different
environments without having to worry about environment-specific performance
differences.
Version control data and models
Version control is like a time machine for your data and models. By keeping
track of changes over time, you can go back to specific versions used for
experiments or deployment. This helps with reproducibility and allows teams to
test different versions to find the best one.
Mixed, autonomous teams
Mixed teams consist of diverse experts who work together on ML models. Each
team member has autonomy over their area of expertise, leading to more
efficient collaboration and better overall coverage during the lifecycle of a
model.
Peer reviews, peer reviews and more peer reviews | scraping/output/-1256552881048572912.txt | [
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Peer reviews, peer reviews and more peer reviews
Reviewing and giving feedback on team members' work is important for
maintaining quality and consistency. For example, code reviews help identify
any bugs or mistakes before they impact the final solution and are a great
opportunity to learn from each other.
## In practice
By integrating MLOps best practices into all of our projects, we help you
realize the full potential of AI in the most effective way possible.
We can also guide you in improving your current approach to MLOps by aligning
the solution with your infrastructure and specific needs. No MLOps solution
fits all, but we can use our expertise to help you create the best MLOps
solution possible.
## Resources
View all
Placeholder tag
Promoting Code Across Environments for Reliable and Efficient Model Deployment
Implementing ML models' code promotion across environments using CI/CD
pipelines.
February 8, 2024
By
Miro Goettler
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Explore the field of Hybrid AI, combining machine learning and expert rules
for optimal outcomes. Learn its relevance, integration methods, and real-world
examples.
October 17, 2022
By
Matthias Feys
Placeholder tag
Why every AI project needs an MLOps ecosystem in place
This blogpost covers the need for MLOps and how it helps to manage the
complexity of machine learning models and deployments. Secondly, it addresses
the business implications of implementing MLOps as a proper ecosystem. Lastly,
the challenges of building an MLOps capability are covered to ensure the
success of your machine learning initiatives at your organisation.
November 1, 2022
By
Placeholder tag
Vertex Pipelines — Vertex AI vs AI Platform | scraping/output/-1256552881048572912.txt | [
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November 1, 2022
By
Placeholder tag
Vertex Pipelines — Vertex AI vs AI Platform
Data Engineer Liam takes a look at how Pipelines can be deployed on the new
and improved GCP product, Vertex AI Pipelines. The recently released tool
takes a more managed approach to Pipelines in GCP, which promises to make
running MLOps pipelines in the cloud easier than ever.
August 31, 2021
By
Liam Campbell
Placeholder tag
Vertex AI is All You Need
Deploying a Scikit-learn Pipeline + LightGBM Classifier Model on Vertex AI for
Explainable Online Predictions
October 26, 2022
By
Placeholder tag
Pharma 4.0 : Impact drug manufacturing with AI in Life Science Industries
In this blog, we will uncover some pressing challenges within the Life Science
manufacturing industry and how breakthroughs in Machine Learning techniques
offer measurable returns.
April 28, 2021
By
Life Sciences & Healthcare
Placeholder tag
Getting model predictions from Vertex AI and how it compares to AI Platform | scraping/output/-1256552881048572912.txt | [
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] |
April 28, 2021
By
Life Sciences & Healthcare
Placeholder tag
Getting model predictions from Vertex AI and how it compares to AI Platform
We take a look at how models can be deployed and used for prediction on the
new and improved GCP product, Vertex AI. The platform was launched a couple of
weeks ago and aside from adding additional features, existing features such as
serving models for predictions have been updated and improved. We take a look
at how endpoints are now a central part of model predictions and how
containers have made deploying custom models very straightforward.
June 9, 2021
By
Rebekka Moyson
Placeholder tag
Boosting your Manufacturing Process using AI with Minimum Investment | scraping/output/-1256552881048572912.txt | [
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] |
June 9, 2021
By
Rebekka Moyson
Placeholder tag
Boosting your Manufacturing Process using AI with Minimum Investment
AI can make a significant contribution to manufacturing by faster action and
decision making, innovative product, services and material designs, improved
efficiency, higher precision and lower costs. It is time for a change. You can
enable AI without the need for high capital investments or major process
redesigns. You just need to look for the right opportunities to be more
productive and sustainable.
May 3, 2021
By
Jeffrey Hagen
Manufacturing
Large Language Model
Foundation Models
Corporate
People
Structured Data
Chat GPT
Sustainability
Voice & Sound
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Data Protection & Security
Responsible/ Ethical AI
Infrastructure
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MLOps
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Natural language processing
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## Contact Our experts in MLOps for AI Solution deployment and management | scraping/output/-1256552881048572912.txt | [
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The coronavirus crisis is challenging everybody in different ways.
From a technical point of view, the sudden switch to remote working can be
difficult for a lot of companies. A lot of employees and IT teams seem to be
on the verge of a nervous breakdown due to connectivity, VPN and remote
desktop issues. | scraping/output/-5981754466922191164.txt | [
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