Hackernoon logoSelf Driven Data Science - Issue #52 by@conordewey3

Self Driven Data Science - Issue #52

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Conor Dewey

Data Science Intern

Self Driven Data Science — Issue #52

Weekly rundown of interesting news and insights focused on data science, machine learning, and artificial intelligence

Here’s this weeks lineup of data-driven articles, stories, and resources ranging across the broad field of data science while offering value to both beginners and experienced practitioners alike. If you would like this post delivered faithfully to your inbox each week, then go ahead and subscribe. Enjoy!


The Best Mario Kart Characters According to Data Science

Using data science and the concept of Pareto efficiency, this post dives into exploring the most effective Mario Kart player combinations through concise explanations and excellent visualizations.


Model Tuning and the Bias-Variance Tradeoff

Models make mistakes if their patterns are overly simple or overly complex. The long-awaited sequel to their decision tree focused initial post, R2D3 explains tuning and the Bias-Variance tradeoff.


Add Constrained Optimization To Your Toolbelt

The team at Stitch Fix shows how optimization modeling can be applied to real problems. This post is an introduction to constrained optimization aimed at data scientists and developers fluent in Python, but without any background in operations research or applied math.


5 Reasons Logistic Regression Should Be the First Thing You Learn as a Data Scientist

The author makes a strong argument for the importance of Logistic Regression as a tool for learning fundamental data science concepts, especially when it comes to learning the basics of the ETL pipeline.


The Trouble with D3

This post touches on a common misconception that d3 and data visualization are the same thing by emphasizing how d3 is a toolkit for communicating complex data-driven concepts on the web.

Source: xkcd

Any inquires or feedback regarding the newsletter are greatly encouraged. Feel free to reach out and follow me on LinkedIn, Medium, Twitter, or check out some more content at my website.

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Thanks for reading and have a great day!



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