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Introduction This blog is a part of the learn machine learning coding basics in a weekend . We recommend the book Python Data Science Handbook… Read More »Python machine learning libraries

This article is a solid introduction to statistical testing, for beginners, as well as a reference for practitioners. It includes numerous examples as well as… Read More »Tutorial: Statistical Tests of Hypothesis

Here we describe a simple methodology to produce predictive scores that are consistent over time and compatible across various clients, to allow for meaningful comparisons… Read More »How to Stabilize Data Systems, to Avoid Decay in Model Performance

It all depends on the classes that you attended. Some are worth listing, some are best not to mention. Here I review of few of… Read More »Should you Add your Coursera, Udacity, or DataCamp Training to your Resume?

In practice, the Data Scientist wants to know which formula they will write in their Excel sheet when they enter all the data available into… Read More »And Monty Hall Went Bayesian…

Grab a copy of The Elements of Statistical Learning (“the machine learning bible”) and you might be a little overwhelmed by the mathematics. For example, this… Read More »Math You Don't Need to Know for Machine Learning

This article was written by Jason Brownlee.  Artificial neural networks have two main hyperparameters that control the architecture or topology of the network: the number… Read More »How to Configure the Number of Layers and Nodes in a Neural Network

This article was written by Enda Ridge. Data Scientists need to communicate without jargon so customers understand, believe and care about their recommendations. Here is a… Read More »Data Science Jargon Explained to the Layman

This article was written by Vitaly Shmatikov.  Machine learning is eating the world. The abundance of training data has helped ML achieve amazing results for… Read More »What Are Machine Learning Models Hiding?