teleren/devto huggingface dataset:
Voice Based Email Service for Visually Impaired People
Tags: octograd2020
Published: 2020-05-20 06:57:37

Project Title: Voice Based Email Service for Visually Impaired People

Objectives:
    The objective is to create a voice based email service for 
    visually impaired people that will complete the following task:

     1. Creating a dynamic and responsive cloud based email platform.
     2. Integrating text-to-speech and speech-to-text API to the 
        platform.
     3. Compose, read and send emails through voice commands.
     4. Login through voice commands.
     5. Complete dashboard for all the basic email functionalities able 
        to navigate through various mouse click combination.
     6. Maintain a database for all the user and email information.
     7. Help the visually challenged peoples of the society to use one 
        of the most important communication medium of internet i.e 
        email.

Development Languages:
    The languages that will be used to develop this platform is given 
    below:

    1. PHP 7.
    2. Laravel Framework 6.
    3. MySQL 8.
    4. Javascript.
    5. Jquery 3.
    6. Bootstrap 4.
    7. HTML 5.
    8. CSS 3.

Github repository: {% github https://github.com/jobayedsumon/vmail %}
Graduation '20
Tags: octograd2020
Published: 2020-05-20 06:57:22

It was a great experience to be a part of the founding cohort of Plaksha Tech Leaders Fellowship.

I loved studying here and learning not just tech skills but also leadership skills.

My final project was based on finding songs with similar meanings across languages.

The link to the code can be found here :
https://github.com/shivamras304/LyricsMatch_DataX1
 
And the demo can be found here : 
https://lyricsmatch.herokuapp.com/

We have built a song discovery platform to recommend songs in English and Hindi that are closest to the query song in terms of the lyrics. A multilingual sentence encoder - LASER, pre-trained on 93 languages was used to  encode  all the Hindi and English language lyrics that we obtained. Similar songs across language are found using approximate similarity search provided by FAISS. 

All in all, I had an amazing time not just during my project but throughout the course of my fellowship. I'm extremely grateful to have undergone through this experience.
stay safe, stay clean
Tags: octograd2020, devgrad2020, githubsdp
Published: 2020-05-20 06:57:17


[Note]: # (If you used the GitHub Student Developer Pack on your project, add the "#githubsdp" tag above. We’d also love to know which services you used and how you used it!)

## My Project

I worked on this project with a friend at Vandyhacks a few years ago. It is an Android app that plots heat maps of cities across the US representing frequency of occurrence of diseases and alerts you when in proximity of a susceptible trigger. I suppose it's especially relevant given COVID-19, but we since stopped maintaining the project and took it offline. However, we did use Heroku to host it while it was live, a nice benefit offered by the Github Student Developer Pack. We won a sponsor prize (Microsoft) for building this project. 

## Link to Code

https://github.com/vivekvaidya/staysafestayclean
https://github.com/teja635/vandy_hacks

## How I built it

36 hours of energy drinks : )
Tirta Jaya Shopping, Delivery Application
Tags: octograd2020
Published: 2020-05-20 06:52:59

[Comment]: # (All of this is placeholder text. Use this format or any other format of your choosing to best describe your project and experience.)

[Note]: # (If you used the GitHub Student Developer Pack on your project, add the "#githubsdp" tag above. We’d also love to know which services you used and how you used it!)

## My Final Project
I built application to take order of bottled water. This application helps customer to make order to the store, and the store will delivery the order.

## Demo Link
https://play.google.com/store/apps/details?id=id.co.tirtajaya.customer

[Note]: # (Our markdown editor supports pretty embeds. If you're sharing a GitHub repo, try this syntax: `{% github link_to_your_repo %}`)

## How I built it
I build this application using Flutter for the front-end.
In back-end, I use CodeIgniter, MySQL, and Firebase.

## Additional Thoughts / Feelings / Stories
This project consume 1 year to complete, and makes my graduation late about 1 year and 6 months :(.


[Final Note]: # (CONGRATULATIONS!!! You are amazing!)
What is CISSP?
Published: 2020-05-20 06:51:34

# What is CISSP?
CISSP or Certified Information System Security Professional is a globally recognized certification offered by the ISC2 (International Information Systems Security Certification Consortium). The certification validates a candidate's ability and expertise in all fields of information security.

## What is the CISSP Concept?
The CISSP constitutes various topics under information security studies. The final examination is based upon a Common Body of Knowledge (CBK) – a taxonomy or collection of relevant topics for IS security professionals worldwide. The CBK is a large framework of terms and principles allowing professionals worldwide to debate, discuss and solve situations relevant to common information security understanding.

## What are the advantages of CISSP Training?
It's a step up from the Security+ cert and validates everything you'd typically learn in your first four years as a security professional. The CISSP is a great next step beyond either of these two exams. ... If you have broad infosec experience, you're good to start with the CISSP

### Here is Some resources that i listing that some of free to use
[Udemy.com paid!](https://www.udemy.com/course/cissp-domain-1-2/)
[Offerz.Guru Free!](https://offerz.guru/coupon/100_off_cissp_master_class_become_a_cissp_today_free-69)

### for Free courses you can visit link below
[Offerz.Guru](https://Offerz.Guru)

thank you
Social Scraper #githubsdp
Tags: octograd2020
Published: 2020-05-20 06:51:26

Detection of Child Predators/Cyber Harassers on Social Media

## Introduction
The tool intends to identify the cyber predators/child harassers on social media with a malevolent intend. The posts, comments and followers on social media are subjected to analysis using Artificial Intelligence, Machine Learning with IGPL and NSFW(Not Safe For Work) to categorize the offensive contents.

![Tool Working](https://drive.google.com/uc?export=view&id=1y2SVImVtBh_kviigOfFg2Sj2NP98i7Wr) 

This system is capable of analyzing all social media platforms like Instagram, Twitter, Facebook, etc., and other outlets seeking the same suspect. If the suspect doesn’t have the same user ID on different platforms, then Reverse Image Searching is done to identify the suspect. A set of user_id is used as a key to grab their personal information and their post information(Post ID, Comments, Timestamp, location, Captions) from multiple social platforms using ​ OSINT(Open Source INTelligence) and Beautifulsoup Python Package.

## Demo Link - Link to Code
{% github https://github.com/Aravindha1234u/SocialScraper %}


## Analysis

The above data of various posts are subjected to analyze malevolent contents using Machine Learning and Pandas Python library. Based on the statistical analysis, suspects are categorized based on their behavior(also Polite harassment). The users whose suspect level is greater than the threshold value will be scrutinized and monitored for further analysis. The suspected user’s post information(media like Image, Audio, and Video) is retrieved and analyzed using the ​ IGPL Python package, ​ Urllib and ​ Artificial Intelligence with ​ NSFW (Not Safe For Work) library to make them fall under the category ‘suspects/predators’. Finally, the Child grooming patterns followers and statistical results that are generated are analyzed and the concerned person is classified as predator and reported to the law enforcement authorities

![Analysis](https://dev-to-uploads.s3.amazonaws.com/i/vor2mikwmwdxexphi63p.png)

## Conclusion

The suspected user’s post information(media like Image, Audio, and Video) is retrieved and analyzed using the ​ IGPL Python package, ​ Urllib and ​ Artificial Intelligence with ​ NSFW (Not Safe For Work) library to make them fall under the category suspects/predators. Finally, the Child grooming patterns followers and statistical results that are generated are analyzed and the concerned person is classified as predator and can you automatically reported to Gmail address which has been stored in the server.

![Image](https://dev-to-uploads.s3.amazonaws.com/i/6vi6fauzmzxx0sgvah3g.png)

![Image](https://dev-to-uploads.s3.amazonaws.com/i/lylc49kfuuzlvp5hq5mj.png)
watchyourfac.es
Tags: devgrad2020, octograd2020
Published: 2020-05-20 06:51:21

[Comment]: # (All of this is placeholder text. Use this format or any other format of your choosing to best describe your project and experience.)

[Note]: # (If you used the GitHub Student Developer Pack on your project, add the "#githubsdp" tag above. We’d also love to know which services you used and how you used it!)

## My Final Project
Wasn't our final project but we developed an edge based face recognition system. You could upload a photo of a person of interest and train a face recognition model with it. This model was then distributed to our edge devices (a Rapsberry Pie with a webcam). 

Unlike most face recognition systems we leveraged fog computing, meaning that the face recognition happened on the edge device itself. This means that data was being transferred to the backend only in case a match was found, thus providing better privacy.

We also added things like immutable logs and four-eyes principle to every action in order to facilitate accountability.

## Demo Link
https://watchyourfac.es/

## Link to Code
https://github.com/pwillmann/watch-your-face 
[Note]: # (Our markdown editor supports pretty embeds. If you're sharing a GitHub repo, try this syntax: `{% github link_to_your_repo %}`)

## How I built it (what's the stack? did I run into issues or discover something new along the way?)
Authentication: auth0
Backend: AWS IoT, DynamoDB, Lambda 

## Additional Thoughts / Feelings / Stories


[Final Note]: # (CONGRATULATIONS!!! You are amazing!)
A project I built when I was a student: GitHub Graduation 
Tags: github, machinelearning, ddevgrad2020, octograd2020
Published: 2020-05-20 06:48:55

## My Final Project

During my internship at Microsoft (Summer 2018), I got to build a fake news detector with a couple of other people during a week-long hackathon. The purpose of this project was to be able to take a video like the presidential debate and, in real-time, fact-check all of the candidate's statements and provide some level of truth to the audience. The project was built using React, MySQL, Django, Python NLP libraries, and the Federal Reserve Economic Data for our knowledge base.


## Demo Link and Code
 
Link to the demo we showed to Politico: https://antpowell.github.io/DisclAImer/?fbclid=IwAR2iE9hhhdvnY4GiOxFby6sL64p9zolwF83VRqEuhFtvIh3rCPtHUNZkZBc . NOTE: Since we are running jobs in real-time, please don't skip around the video, watch it from the beginning to the end. Facts start to get checked, and comments show in the chatbox around 25 seconds. Since Microsoft decided to continue conversations with Politico to figure out if they wanted to invest in this idea, I am unable to share the source code at this time.


## How I built it (what's the stack? did I run into issues or discover something new along the way?)

In terms of the logistics/how it works, when someone uploads a video, we first run a python job to convert the audio to a transcript. We then run a couple of NLP jobs to find keywords in the transcript (like unemployment or debt ceiling) that can be objectively measured. Once we find some of these keywords, we can then look at the surrounding words and sentences for context (like the candidate saying he/she helped decrease the unemployment rate by,5% etc.). We then aggregate all the statements we want to fact check and then run web scraping jobs against FRED to figure out what the current value for a given statement is (like the standard deduction for everyone). We can then present any images or information we find to the user in the chatbox.

[Final Note]: # (CONGRATULATIONS!!! You are amazing!)
My 'man' command telegram bot
Tags: octograd2020
Published: 2020-05-20 06:47:56

## Introduction
A friend introduced me to the chatting app Telegram a few months back so we could work on a project, and so I started to look into their bot program. After talking about the [Windows Subsystem for Linux](https://docs.microsoft.com/en-us/windows/wsl/install-win10) I got curious if I could make some Linux commands through Node.

## Demo Link
Well, the best demo is by your own hands, you can add it to telegram with [the invite link](https://t.me/Manual_Page_Bot).

Or if you'd like here's a (low-res) gif:
![Alt Text](https://dev-to-uploads.s3.amazonaws.com/i/ol4118dc9pfm0zmp0obv.gif)

## Link to Code
`{% github kouzios/telegram-man-page-bot %}`

## How I built it
It's a simple bot with Node.js and note-telegram-bot-api. There were certainly some issues with the `man` output being too large for Telegram, so I by default output the gnu link for the command instead. However, if you want the text output, shortened, it could be achieved with a `-v` or `--verbose`. So it all worked out in the end. 

## Additional Thoughts / Feelings / Stories
As much as I would like to show off my final project, there's no live demo - as it's a proof of concept for an organization. I don't want to show it off in case it doesn't come to fruition, but I figured I could show off a small project I was working on over the school year.
Yoga Guru - My Final Year Project
Tags: octograd2020
Published: 2020-05-20 06:47:50

## About Yoga Guru
Yoga Guru is your personalized yoga trainer app based on Flutter. It uses poseNet, a pre-trained deep learning model, to estimate body poses in real-time and predict yoga asanas.

## Link to Code
{% github https://github.com/BetaPundit/Yoga-Guru %}


## How I built it (The Story)
- The idea came to me when I first saw the PoseNet framework which is a computer vision model that estimates the pose of a person in an image or a video by estimating where key body joints are. 

- I started by wireframing the app and designed different app screens. 

- I then built different components in Flutter and then used the Flutter Tflite package to run a pre-trained PoseNet model on the image stream (video frame).

- Then I trained a custom model on the output of the above PoseNet model to classify Yoga Poses. It certainly took some time to find images on google to create a dataset and fit a classifier on it.

- The challenge now was to run the 2 model (PoseNet and the custom Yoga Classifier) in a pipeline in the app. For this, I had to understand how to write platform-specific code in Flutter and run custom Tflite models in Android!

- It was a challenging task but in the end, all the hard work paid off and the app was up and running! 


## Additional Thoughts
The art of practising yoga helps in controlling an individual's mind, body and soul. It brings together physical and mental disciplines to achieve a peaceful body and mind. Thus, by building this app, I wish that everyone can access and learn Yoga and keep their body, soul and mind in tune.

Any contributions to the app are most welcome!
Online Playground Vueply
Tags: octograd2020, javascript, typescript, vue
Published: 2020-05-20 06:46:36

Vueply is a experimental online playground, which was created for learning and programming in the web. The main reason, why i built this WebApp is because, I want to launch a course section with "homeworks". For getting started without any tools you can directly jump into that online playground and test your knowledge and start coding.

Vueply supports Vue.js, JavaScript, TypeScript, HTML, CSS and Markdown. Currently, I am working hard on supporting Python and live code for this online playground.
With live code you can simply connect yourself with a friend and solve a problem together.
In additional, right now everything runs in the browser and nothing is stored on any server (that will change with live code and python).

The goal behind Vueply is not to replace the popular choices Sandbox or any other playground. The goal is to work good, fast and easy for beginners. So they can code while they're watching a course.

## Demo Link

You can visit the online playground [here](https://daycademy.github.io/vueply/)

## Code

https://github.com/daycademy/vueply/

## Techstack

I've built this online playground with JavaScript/TypeScript and Vue.js. Vue.js uses typically libraries like Vue Router and Vuex. Furthermore, the server uses TypeScript with Express and Socketio.
Contributing to the Open Source Community for the first time
Tags: octograd2020, showdev, devgrad2020, opensource
Published: 2020-05-20 06:46:09

## My Favorite Project
I would like to speak about my favorite project during which is **also my first contribution to open source community** I worked on during my last year of Computer Science B.Tech degree. I was searching for internships to gain industrial exposure. Fortunately, I was going through my timeline on Linkedin and came across the open-source projects post. Open source was in my mind for a very long time. But I’ve never contributed to it. I found out that the platform is to welcome new open source developers. I was highly exuberant and applied for it immediately.
I contributed for at least a 3-month for the open-source project. The project I worked on is developing an Android App called Travel Mate. 

**Travel Mate** is an android app for travelers. It provides features like choosing the correct destination, making bookings, and organizing the trip. It provides solutions for every problem a traveler might face during their journey. It provides a comprehensive list of information about a destination: current weather, best places to hang out, and the city's current trends.

## Demo Link
 You try your hands on by downloading it from google play store [here](https://play.google.com/store/apps/details?id=io.github.project_travel_mate).

## Link to Code
{% github https://github.com/project-travel-mate/Travel-Mate %}

## How I built it (what's the stack? did I run into issues or discover something new along the way?)
The stack I worked on was completely Java and the project uses some of the open-source libraries to support its functionalities and improve performance. It was initially difficult getting used to the environment (Fixing the merge conflicts 😜) as I was not very familiar with git and all the projects were on GitHub, but with the support of the mentors, it became a piece of cake.
I was so excited to submit the first PR in GitHub. This went on for 2 months. I was highly motivated by my fellow contributors as they were equally competing with me. Their enthusiasm triggered me to participate and contribute more to Open Source. Thanks to the mentors who were very helpful.


## Additional Thoughts / Feelings / Stories
It was great to still be the top contributor to the Project Travel Mate right after the organization owners.
Below are some of the points I got in return by contributing to open source:
* Excellent experience of working on a real-world project.
* Learned how things are done professionally.
* Being an Open Source contributor to some of the coolest projects on GitHub.
* Chance to get mentored by some of the best software developers from tech giants. I was mentored by **Adobe** and **Amazon** developers.

Here is the [link](https://github.com/project-travel-mate/Travel-Mate/graphs/contributors) for my contributions to the open-source project. 

I would like to thank **Github** for providing such an awesome platform to contribute to open-source.
Blood Cancer Diagnosis
Tags: octograd2020
Published: 2020-05-20 06:43:12

[Comment]: # (All of this is placeholder text. Use this format or any other format of your choosing to best describe your project and experience.)  

[Note]: # (If you used the GitHub Student Developer Pack on your project, add the "#githubsdp" tag above. We’d also love to know which services you used and how you used it!)  

## My Final Project
Cell classification via image processing has recently gained interest from the point of view of building computer assisted diagnostic tools for blood disorders such as leukemia. In order to arrive at conclusive decision on disease diagnosis and degree of progression, it is very important to identify malignant cells with high accuracy. Computer assisted tools can be very helpful in automating the process of cell segmentation and identification. Identification of maIignant cells vis-à-vis normal cells from the microscopic images is difficult because morphologically both cells types appear similar.  

As a consequence, leukemia (blood cancer) is detected in advanced cancer stages via microscopic image analysis, not because of the ability to identify these under the microscope, but because of the medical domain knowledge, i.e., the cancer cells start growing in an unrestricted fashion and hence, they are present in much more larger numbers as compared to their numbers in a normal person. So, in this project, I was supposed to train a model which can diagnose the cancer cells in a very effective manner. I tried training various models on the basis of their architecture as our model must learn the most minor details from the data. Before training them, I tried a lot of hyper parameter tuning in order to get the best results. After using various network architectures like CNN, ResNet50, Capsnet, SeResNext, DenseNet, ResNext50, VGG19 while also using stacking. I found that SeResNext network architecture was doing really great in comparison to other architectures. The comparison between all these architectures can be found in the link provided. It got an accuracy of about 90% in predicting if a Blood Cell in cancerous or not.  

After the model building, I created an Flask API of the same and then created a Docker image of it.  

## Link to Code

{% github https://github.com/saarques/AI-Without-Borders---Projects %}

[Note]: # (Our markdown editor supports pretty embeds. If you're sharing a GitHub repo, try this syntax: `{% github link_to_your_repo %}`)  

## How I built it (what's the stack? did I run into issues or discover something new along the way?)  

I built this project using Deep Learning(Keras, Tensorflow, Scipy, Scikit-learn, pandas, numpy), Flask and Docker. I got into many issues and resolved them with the help of peers and ofcourse Stack Overflow! :3  

## Additional Thoughts / Feelings / Stories

I hope that this project will be useful in the future of medical diagnosis of Blood Cancer.  

[Final Note]: # (CONGRATULATIONS!!! You are amazing!)
[MY Project]
Tags: octograd2020
Published: 2020-05-20 06:43:08

[Comment]: # (All of this is placeholder text. Use this format or any other format of your choosing to best describe your project and experience.)

## My Final Project
Presently I'm in the final year of my graduation, I've done a project (Group of 4) in analyzing the Ground Level Water, to identify the water scarcity in a particular region. This is a small project but I was happy that I was able to complete this. This project deals with technology stacks like Python, Machine Learning where we used Logistic Regression to classify the ground water scarcity (Classification categories like 'Critical', 'Semi-Critical', 'Moderate', etc.)

## Link to Code
`{% github https://github.com/rgdeekshith/Ground-Water-Level-Analysis-and-Prediction %}`

## How I built it (what's the stack? did I run into issues or discover something new along the way?)
I built it using Python tools like Pandas, Numpy, Matplotlib, Seaborn, Scikit-Learn which are basic tools. I was new to python language,  that itself was a barrier to compete in the projects, after practicing from websites like hackerrank, coursera etc, I was able to overcome the deficits.


## Additional Thoughts / Feelings / Stories
After the completion of the project, i felt like I excelled some part of the Machine Learning Domain that made me to passionately concentrate on the technologies related to ML.


[Final Note]: # (CONGRATULATIONS!!! You are amazing!)