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Updated by claireelizabethwhit on Jan 26, 2019
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Machine Learning Python Tutorials

Want to learn how to implement machine learning on your data? Check out these tutorials from across the internet!

How to Improve Deep Learning Model Robustness by Adding Noise

Adding noise to an underconstrained neural network model with a small training dataset can have a regularizing effect and reduce overfitting.

How to Make Awesome Recommendations with Apriori Algorithms

A recommendation algorithm you can use with python is the apriori algorithm. This tutorial will explain the apriori math and show you how to implement it.

Introduction to Monte Carlo Tree Search: The Game-Changing Algorithm behind DeepMind’s AlphaGo

In this article, learn how the algorithm behind DeepMind's popular AlphaGo and AlphaGo Zero programs works - Monte Carlo Tree Search.

How to Create a Random-Split, Cross-Validation, and Bagging Ensemble for Deep Learning in Keras

It is important in ensemble learning that the models that comprise the ensemble are good, making different prediction errors. Predictions that are good in different ways can result in a prediction that is both more stable and often better than the predictions of any individual member model.

How To Implement the Top Clustering Algorithms in Python

Clustering algorithms are a powerful machine learning technique. This tutorial teaches you how to implement K-Means and Thompson Sampling in python.

A Gentle Introduction to the Rectified Linear Activation Function for Deep Learning Neural Networks

In a neural network, the activation function is responsible for transforming the summed weighted input from the node into the activation of the node or output for that input.

Get Started with PyTorch – Learn How to Build Quick & Accurate Neural Networks (with 4 Case Studies!)

Learn what PyTorch is, how it works, and then get your hands dirty with 4 case studies. You'll become quite nifty with PyTorch by the end of the article!

How to Understand and Implement Regression Analysis

They say a picture speaks 1000 words. So to summarize regression analysis, I've created an infographic. But first what is regression analysis?