// My 5 Favorite Data Science Portfolios · Learning With Data

My 5 Favorite Data Science Portfolios

Oct 13, 2019 02:58 · 626 words · 3 minute read data science portfolio

Photo by Aziz Acharki on Unsplash Photo by Aziz Acharki on Unsplash

Earlier this week, I posted an article on How to Create an Amazing Data Science Portfolio:

How to Create an Amazing Data Science Portfolio
_To showcase your work and stand out_towardsdatascience.com

At the end of the article, I posted a link to an example portfolio that I liked by Tim Dettmers. Afterward, I had a few people ask me to compile a larger list of great data science portfolios and projects. So — here we go! My 5 favorite data science portfolios.


While not a portfolio, but rather a project, I think this is a great format to try and exemplify.

iSee: Using deep learning to remove eyeglasses from faces
_Melissa Runfeldt is an Insight alumna from the Summer 2016 Silicon Valley Data Science session, where she built a deep…_blog.insightdatascience.com

Melissa Runfeldt did a great job defining and motivating her problem, discussing how she gathered data and explaining her methods with images of results. All in a way that would be easy for a non-technical person to follow (at least at a high level). One thing I thought was missing, though, was a link to the code.

Fake News Classifier

This is a more advanced way to showcase a project, but I believe it is really well done.

Make News Credible Again
_Meet the team behind the project. Graduates from UC Berkeley’s Masters in Information & Data Science program, we are…_makenewscredibleagain.github.io

The website provides a nice, simple overview of the approach and even a way to have your own news articles classified (though, it now appears to be broken). Also, the website links to a series of Medium articles that go into more depth on the approach and results. Again, though, I had trouble finding any links to the code the team wrote.

Stanford Machine Learning Projects

This example is not a portfolio of a person, but rather of a class. The machine learning class at Stanford consists of a project and the reports and posters can be seen online:

CS229: Machine Learning - Projects Fall 2018
_Edit description_cs229.stanford.edu

Here you will find a lot of really nice reports such as the one on Eluding Mass Surveillance: Adversarial Attacks on Facial Recognition Models. This report is more academic in its nature but does a great job explaining the problem, data, and experimental results. It even links to the code on GitHub!


FastML is a great website run by Zygmunt Zając.

_Everybody had the fantasy of predicting the stock market. We investigated the subject in Are stocks predictable?. In…_fastml.com

In his own words, “FastML probably grew out of a frustration with papers you need a Ph.D. in math to understand and with either no code or half-baked Matlab implementation of homework-assignment quality.” One of his most popular posts is Deep learning made easy and does a good job discussing deep unsupervised learning and links to code.

Lego Sorting

This project is amazing!

Lego Sorter using TensorFlow on Raspberry Pi
_In early 2017 I stumbled across one of the documented Google Cloud and Tensorflow use cases titled How a Japanese…_medium.com

Not only is it a really cool idea that involved 200 hours spread across 6 months, but he also took the time to create an amazing explanation of the entire process on Medium. He even uploaded the datasets he created to Kaggle! If you are looking for the gold standard in data science projects, this is definitely it.


I hope my attempt to showcase some of the data science projects and portfolios that have inspired me will also help you go and create something awesome! If you have other examples that you love or even your own, please put them in the comments so everyone can enjoy them!

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