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 Machine Learning Cheat Sheets
By Matthew Mayo, KDnuggets Managing Editor on September 11, 2018 in Cheat Sheet, Deep Learning, Machine Learning, Mathematics, Neural Networks, Probability, Statistics, Supervised Learning, Tips, Unsupervised LearningCheck out this collection of machine learning concept cheat sheets based on Stanord CS 229 material, including supervised and unsupervised learning, neural networks, tips & tricks, probability & stats, and algebra & calculus.
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5 Things to Know About A/B Testing
This article presents 5 things to know about A/B testing, from appropriate sample sizes, to statistical confidence, to A/B testing usefulness, and more.
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 Data Science Cheat Sheet
Check out this new data science cheat sheet, a relatively broad undertaking at a novice depth of understanding, which concisely packs a wide array of diverse data science goodness into a 9 page treatment.
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A Crash Course in MXNet Tensor Basics & Simple Automatic Differentiation
This is an overview of some basic functionality of the MXNet ndarray package for creating tensor-like objects, and using the autograd package for performing automatic differentiation.
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The 4 Levels of Data Usage in Data Science
This is an overview of the 4 levels, or "buckets," of data usage in business, starting at monitoring and progressing to automation.
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Automated Machine Learning vs Automated Data Science
Just by adding the term "automated" in front of these 2 separate, distinct concepts does not somehow make them equivalent. Machine learning and data science are not the same thing.
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Building a Basic Keras Neural Network Sequential Model
The approach basically coincides with Chollet's Keras 4 step workflow, which he outlines in his book "Deep Learning with Python," using the MNIST dataset, and the model built is a Sequential network of Dense layers. A building block for additional posts.
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30 Free Resources for Machine Learning, Deep Learning, NLP & AI
Check out this collection of 30 ML, DL, NLP & AI resources for beginners, starting from zero and slowly progressing to the point that readers should have an idea of where to go next.
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Natural Language Processing Nuggets: Getting Started with NLP
Check out this collection of NLP resources for beginners, starting from zero and slowly progressing to the point that readers should have an idea of where to go next.
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Step Forward Feature Selection: A Practical Example in Python
When it comes to disciplined approaches to feature selection, wrapper methods are those which marry the feature selection process to the type of model being built, evaluating feature subsets in order to detect the model performance between features, and subsequently select the best performing subset.
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Machine Learning Cheat Sheets
Data Science Cheat Sheet
Automated Machine Learning vs Automated Data Science
30 Free Resources for Machine Learning, Deep Learning, NLP & AI