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Weekly Selection – May 3, 2019

How I Passed the Google Cloud Professional Data Engineer Certification Exam

By Daniel Bourke – 10 min read

Over the past few months, I’ve been taking courses alongside using Google Cloud to prepare for the Professional Data Engineer exam. Then I took it. And I passed. And a few weeks later my hoodie arrived. The certificate came quicker.


Five Machine Learning Paradoxes that will Change the Way You Think About Data

By Jesus Rodriguez – 8 min read

Paradoxes are one of the marvels of human cognition that are hard to using math and statistics. Conceptually, a paradox is a statement that leads to an apparent self-contradictory conclusion based on the original premises of the problem.


Speed Up Your Exploratory Data Analysis With Pandas-Profiling

By Lukas Frei – 5 min read

When importing a new data set for the very first time, the first thing to do is to get an understanding of the data. This includes steps like determining the range of specific predictors, identifying each predictor’s data type, as well as computing the number or percentage of missing values for each predictor.


Creating Bitcoin trading bots using deep reinforcement learning

By Adam King – 12 min read

In this article we are going to create deep reinforcement learning agents that learn to make money trading Bitcoin. In this tutorial we will be using OpenAI’s gym and the PPO agent from the stable-baselines library, a fork of OpenAI’s baselines library.

My Data Science Blogging Journey on Medium till now

By Rahul Agarwal – 9 min read

I first started blogging in 2014 on my blog. And I still remember my first Blog post. It was a disaster. But I remember that it helped some people. And that was probably a good start.


The Fastest Way to Learn Data Science

By Rebecca Vickery – 5 min read

When I first started writing blogs about data science on medium I wrote a series of posts describing a complete roadmap for learning data science. I am largely self-taught in data science and over the last few years have, through trial and error, found some excellent ways to learn in a fast, efficient way.


The easy way to work with CSV, JSON, and XML in Python

By George Seif – 4 min read

Python’s superior flexibility and ease of use are what make it one of the most popular programming language, especially for Data Scientists. A big part of that is how simple it is to work with large datasets.


Python for Finance: Robo Advisor Edition

By Kevin Boller – 14 min read

In this series continuation, I will provide an overview of Robo Advisors and then share additional code and details on how to evaluate a diversified index strategy.


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