Self Driven Data Science — Issue #29

Self Driven Data Science — Issue #29

Here’s this weeks lineup of data-driven articles, stories, and resources delivered faithfully to your inbox for you to consume. Enjoy!

Daniel Tunkelang, who led machine learning projects at Endeca, Google, LinkedIn explains some key concepts and misconceptions about the current state of machine learning.

You can think of Docker as lightweight virtual machines that contain everything you need to run an application. This article serves as a quick primer so you don’t have to parse all the information out there and instead can learn the things you need to know to quickly get started.

8 Ways to do Linear Regression and Measure Their Speed

It is critical for data scientists to be aware of the various methods they can use to quickly fit a linear model. This article analyzes the effectiveness and scalability of several popular options out there.

Source: xkcd

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Thanks for reading and have a great day!


Self Driven Data Science — Issue #29 was originally published in Hacker Noon on Medium, where people are continuing the conversation by highlighting and responding to this story.

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Gurupriyan is a Software Engineer and a technology enthusiast, he’s been working on the field for the last 6 years. Currently focusing on mobile app development and IoT.