Low-Code is the next big thing in Data Science! What do you think?

Issue #2. 3 Side Projects, 3 Open Source Projects, 3 Competitions. Introducing Trello Roadmap, Contributors, and other sections.

First of all, a warm welcome to all the new subscribers of this Newsletter. We are now a community of 50+ Data Enthusiasts. ❤

I’m glad we are growing as a community very fast! Thanks for your tremendous support and engagement with our last issue.

This week, we decided to introduce new sections and this will be our template, more or less, in the future issues as well. I’d love to hear your opinions on this! Reply to this issue and let us know what you think of the format and the resources we are sharing. 😊


Here’s what’s inside this issue:

3 Side Projects
3 Open Source Projects
3 Competitions
What else is going on?
Parting thoughts

Every week the topics we cover might differ so that we cover what’s necessary and also important. For example, I might replace the ‘Competitions’ topic with ‘Datasets’ in next week’s issue. So, let’s dive in and see what’s in store for us this week!


3 Side Projects 🛠

  1. End to End Machine Learning Tutorial — From Data Collection to Deployment 🚀 | Ahmed Besbes | End-To-End, NLP

Learn how to build and deploy a machine learning application from scratch: an end-to-end tutorial to learn to scrape, training a character-level CNN for text classification, building an interactive responsive web app with Dash and Docker, and deploying to AWS. You're in for a treat!

  1. Master Web Scraping Completely From Zero To Hero 🕸 | Abhay Parashar | Python, Web Scraping

It is common knowledge among Data Scientists that we spend 80% of our time managing and cleaning Data. But, before that, shouldn’t we have the data with us? That’s where the skills of Web Scraping comes in. In this project, you’ll be mastering Web Scraping by learning how to scrape and collect data using Beautiful Soup and Requests Library which is required for your next side project.

  1. Topic modeling visualization – How to present the results of LDA models? 📊 | Selva Prabhakaran | NLP, Data Visualization

If I give you a dataset of 1000 Newspapers and ask you to find me the common topics in those newspapers. How will you do it? Going through the newspapers and noting down the topics is out of the question. This tutorial introduces you to Topic Modeling and how to visualize those topics. Have fun with this one!


3 Open Source Projects 📖

  1. Monk - A computer vision toolkit for everyone 🧘‍♂️ | Tessellate Imaging | Computer Vision, Low-Code

Are you a beginner in Computer Vision? Don’t want to go through complex CNN Structures to get started with your CV Side Projects? Monk is a low-code tool that enables Data Scientists to explore Image Datasets and helps them build prototypes before diving deep into complex CNN Architectures. It is especially useful if you’re looking to participate in Competitions. Check this step-by-step tutorial by me on how I used the Monk toolkit for Image Classification.

  1. Lazy Predict 👀 | Shankar Pandala | Machine Learning, Low-Code

It is important for people in the Data Science profession and especially Business owners to whip up quick prototypes in order to understand whether an ML Model will solve the problem at hand or not.

Lazy Predict helps build a lot of basic Machine Learning Models with low-code and helps understand which models work better without any parameter tuning. Check this example by the author on building Regression Models in less than 10 lines of code.

  1. AI Text Gen using GPT-2 💬 | Max Woolf | Deep Learning, NLP

Everyone is itching to try GPT-3 but looks like we have to wait until everyone gets access to its beta version. So, why don’t you try this cool project to generate text using AI? It is a robust Python tool for text-based AI training and generation using OpenAI's GPT-2 architecture.

It leverages PyTorchHugging Face Transformers, and PyTorch-lightning with specific optimizations plus many added features.


3 Competitions 🤛

  1. 2020 Kaggle ML & DS Survey 🗣 | Kaggle | Story-telling

Kaggle set out to conduct an industry-wide survey that presents a truly comprehensive view of the state of data science and machine learning. After cleaning the data, they ended up with 20,036 responses!

The results include raw numbers about who is working with data, what’s happening with machine learning in different industries, and the best ways for new data scientists to break into the field.

Kaggle is awarding a prize pool of $30,000 to notebook authors who tell a rich story about a subset of the data science and machine learning community. If you’re a story-teller or a beginner in Data Science, this is an amazing opportunity to expose yourselves to Competitions.

Participate by clicking here.
Submission deadline: 11:59 PM UTC, January 6th, 2021.

  1. Cassava Leaf Disease Classification 🍀 | Makerere University AI Lab | Computer Vision

Makerere University AI Lab has recently announced this competition for the prize money worth of $18,000.

As the second-largest provider of carbohydrates in Africa, cassava is a key food security crop grown by smallholder farmers because it can withstand harsh conditions. At least 80% of household farms in Sub-Saharan Africa grow this starchy root, but viral diseases are major sources of poor yields. With the help of data science, it may be possible to identify common diseases so they can be treated.

Participate by clicking here.
Submission Deadline: 11:59 PM UTC, Feb 19, 2021.

  1. HackerEarth Machine Learning Challenge: Love in the time of screens ❤ | HackerEarth | NLP

Just like that, with the blink of an eye, it’s the holiday season again. It’s indeed a wonderful time, no doubt, but is that the case for everyone? Unfortunately, it is not so.

A recently launched online dating site has assigned you the duty of playing Cupid and matching two lovebirds. As a Machine Learning expert, you are required to build a sophisticated model that predicts the match percentage between its users based on multiple attributes such as — their identifiers, preferences, interests, and the like.

Participate by clicking here.
Submission Deadline: Dec 23, 10:30 AM IST


What else is going on?

Here are some updates and features we’re working on to improve the website.

  1. Hemanth is our new Contributor. A big shout out to him for coming forward and helping me through this journey. ❤

  2. Join our Telegram, Instagram, and Twitter for regular updates on Data Science.

  3. Our Trello Roadmap is now available for public access. You can submit your idea or feature request under the ‘Ideas’ card.

  4. Four new Side Projects added to the website.

  5. Working on ‘Wall Of Love’ to gather social proof to let others know how they’re finding the Newsletter and Website useful. Please submit your feedback by replying to get featured on our Website. 😊

  6. Created a Discord Server. Planning to release it to the public by next week.

  7. Working on Contributors/Team page to be added on the website.


Parting thoughts…

So, that’s all for this week. Before I conclude, I would like to ask you guys about this particular idea I’m pondering on.

What do you think about introducing Demo Days to our Discord Server? Students can register and participate in these Demo Days where they get to talk and present about their recent side project. They can gather feedback and improve their speaking skills which adds a ton of value the next time they attend an interview.

What do you think about this idea? Leave a comment and let me know!

Leave a comment

With love,
Vidya.


Was this issue useful? Help us improve!

With your feedback, we can improve the newsletter. Click on a link to vote:


An inexpensive way to support this Newsletter is by sharing it with others or, you could buy me a coffee instead. 😊☕

Share Next Side Project

If this post was forwarded to you, please subscribe:


Follow us on Instagram | Telegram | Twitter
Contact: Vidya | Hemanth
Submit Your Project: Click here
Website: Next Side Project