Self Driven Data Science — Issue #25
Here’s this weeks lineup of data-driven articles, stories, and resources delivered faithfully to your inbox for you to consume. Enjoy!
This post by David Robinson, Data Scientist at Stack Overflow makes a strong argument outlining the key reasons why blogging is well worth your time as a Data Scientist, regardless of your experience level.
Machine learning has been around for a while before deep neural networks took over the scene. This post contains a list of the algorithms you need to know, so you can tackle any problem that comes your way. This isn’t an exhaustive list, but your bases will be mostly covered.
How do we communicate confidences and doubts about data to a non-technical audience (in a way that is efficient and easily interpretable)? This post attempts to answer that question by experimenting with embedding a “state of the data” in presentations through red, yellow, and green data meta-metrics.
This post goes over the basics of Pandas, the most popular data manipulation package for Data Science with Python. The author outlines a strategy to ‘learn pandas’ in a clear and concise way.
In this post, the author describes how he built a classification machine learning algorithm that employs a hierarchical recurrent neural network to isolate specific, relevant content from millions of hours of video. Very cool project that is well worth looking over for inspiration and learning purposes.
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Thanks for reading and have a great day!