Given that machine learning will make up the overwhelming majority of software development and that non-technical people will be exposed to AI systems more and more, one of the main challenges of AI is adapting and enhancing employee skills. It is also becoming necessary to support teaching staff in proactively taking AI's ethical and critical issues into account.
As an open-source company democratizing machine learning, Hugging Face believes it is essential to educate people from all backgrounds worldwide.
We launched the ML demo.cratization tour in March 2022, where experts from Hugging Face taught hands-on classes on Building Machine Learning Collaboratively to more than 1000 students from 16 countries. Our new goal: to teach machine learning to 5 million people by the end of 2023.
This blog post provides a high-level description of how we will reach our goals around education.
🗣️ Our goal is to make the potential and limitations of machine learning understandable to everyone. We believe that doing so will help evolve the field in a direction where the application of these technologies will lead to net benefits for society as a whole.
Some examples of our existing efforts:
- we describe in a very accessible way different uses of ML models (summarization, text generation, object detection…),
- we allow everyone to try out models directly in their browser through widgets in the model pages, hence lowering the need for technical skills to do so (example),
- we document and warn about harmful biases identified in systems (like GPT-2).
- we provide tools to create open-source ML apps that allow anyone to understand the potential of ML in one click.
🗣️ We want to lower the barrier to becoming a machine learning engineer by providing online courses, hands-on workshops, and other innovative techniques.
- We provide a free course about natural language processing (NLP) and more domains (soon) using free tools and libraries from the Hugging Face ecosystem. It’s completely free and without ads. The ultimate goal of this course is to learn how to apply Transformers to (almost) any machine learning problem!
- We provide a free course about Deep Reinforcement Learning. In this course, you can study Deep Reinforcement Learning in theory and practice, learn to use famous Deep RL libraries, train agents in unique environments, publish your trained agents in one line of code to the Hugging Face Hub, and more!
- We provide a free course on how to build interactive demos for your machine learning models. The ultimate goal of this course is to allow ML developers to easily present their work to a wide audience including non-technical teams or customers, researchers to more easily reproduce machine learning models and behavior, end users to more easily identify and debug failure points of models, and more!
- Experts at Hugging Face wrote a book on Transformers and their applications to a wide range of NLP tasks.
Apart from those efforts, many team members are involved in other educational efforts such as:
- Participating in meetups, conferences and workshops.
- Creating podcasts, YouTube videos, and blog posts.
- Organizing events in which free GPUs are provided for anyone to be able to train and share models and create demos for them.
🗣️ We want to empower educators with tools and offer collaborative spaces where students can build machine learning using open-source technologies and state-of-the-art machine learning models.
We provide to educators free infrastructure and resources to quickly introduce real-world applications of ML to theirs students and make learning more fun and interesting. By creating a classroom for free from the hub, instructors can turn their classes into collaborative environments where students can learn and build ML-powered applications using free open-source technologies and state-of-the-art models.
We’ve assembled a free toolkit translated to 8 languages that instructors of machine learning or Data Science can use to easily prepare labs, homework, or classes. The content is self-contained so that it can be easily incorporated into an existing curriculum. This content is free and uses well-known Open Source technologies (🤗 transformers, gradio, etc). Feel free to pick a tutorial and teach it!
We're organizing a dedicated, free workshop (June 6) on how to teach our educational resources in your machine learning and data science classes. Do not hesitate to register.
We are currently doing a worldwide tour in collaboration with university instructors to teach more than 10000 students one of our core topics: How to build machine learning collaboratively? You can request someone on the Hugging Face team to run the session for your class via the ML demo.cratization tour initiative.
- 09/08[EVENT]: ML Demo.cratization tour in Argentina at 2pm (GMT-3). Link here
🔥 We are currently working on more content in the course, and more! Stay tuned!