Self Driven Data Science — Issue #35

The 5 Clustering Algorithms Data Scientists Need to Know

Given a set of data points, we can use a clustering algorithm to classify each data point into a specific group. In theory, data points that are in the same group should have similar properties and/or features, while data points in different groups should have highly dissimilar properties and/or features. This article gives an overview of 5 popular clustering algorithms.

How to Solve 90% of NLP Problems

This article effectively teaches you how to gather, prepare and inspect text data. You’ll be able to build, interpret and understand simple models. This post serves as a step-by-step guide to highly effective standard approaches.

The Zen of Python

Did you know that if you type ‘import this’ into a modern Python interpreter, you get the Zen of Python? Tim Peters’ eternal words of wisdom, often quoted, on the essential truths of Python. This interesting post goes over the history of the easter egg and how it came to be.

Building an Email Classifier For Job Applications

What does a Data Scientist do when he receives a lot of rejection emails? He builds a classifier that automatically sorts emails indicating rejection into the reject category and the other emails into not-reject category. Check out the post outlining the full process of the project.

Introduction to AWS for Data Scientists

Familiarity with Amazon Web Services helps data scientists to prepare the infrastructure they need, easily set up necessary tools, and decrease expenses significantly. In this post, the author gives an overview of useful AWS services for data scientists — what they are, why they’re useful, and how much they cost.

Source: xkcd

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