The Future of AI is in Model Compression

New research can reduce the size of your neural net in a super easy wayPhoto by Markus Spiske on UnsplashThe future looks towards running deep learning algorithms on more compact devices as any improvements in this space make for big leaps in the usability of AI.If a Raspberry Pi could run large neural networks, then artificial intelligence... Continue Reading →

The Future of GIT (2020)

Opinion5 Predictions of what Data Scientists can expectPhoto by Yancy Min on UnsplashVersion Control is a pretty boring topic for most people but for coders and researchers, it’s imperative to understand. The importance of version control is really understood when you work in a big team working on a big project. With multiple users working on the... Continue Reading →

How to Deploy Streamlit on Heroku

OpinionFor Endless Possibilities in Data SciencePhoto by Kevin Ku on UnsplashIn a previous post, I predicted that the popularity of Flask would really take a hit once Streamlit comes more into the mainstream. I also made the comment that I would never use Flask again.I still stand by both of these comments.In that time, I’ve made four... Continue Reading →

4 Awesome COVID Machine Learning Projects

Forward thinking ways to apply Machine Learning in a PandemicPhoto by Neil Thomas on UnsplashNote from the editors: Towards Data Science is a Medium publication primarily based on the study of data science and machine learning. We are not health professionals or epidemiologists, and the opinions of this article should not be interpreted as professional advice. To... Continue Reading →

4 Sorting Algorithms in Python

Including Time Complexities and CodePhoto by Olav Ahrens Røtne on UnsplashHave you ever tried to sort a deck of cards by hand? You probably, intuitively, used the insertion sort algorithm. The following article will explain why this algorithm works and how long it takes. The good news is that you do end up with a sorted set,... Continue Reading →

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