MOOC
- Andrew NG’s Machine Learning course. (Python codes 1 )
Articles
- Machine Learning is Fun! by Adam Geitgey. This article is part of a series. Check out the full series: Part 1, Part 2, Part 3, Part 4, Part 5, Part 6 and Part 7!
Video
- Hello World – Machine Learning Recipes by Google Developers
Handling Missing Data
Feature Selection
- Scikit-learn documentation
- An Introduction to Feature Selection by http://machinelearningmastery.com
- Feature Selection in Python with Scikit-learn by http://machinelearningmastery.com
- An Introduction to Variable and Feature Selection by Guyon and Elisseeff
Feature Extraction
K-Means Clustering
- Introduction to K-Means Clustering
- Understanding K-Means
- K-Means implementation from scratch from Siraj
K-Nearrest Neighbors
- Tutorial to Implement k-nearest neighbors in Python from scratch by Jason Brownlee
- Understanding K-Nearest Neighbors
Naive Bayes
- How the Naive Bayes Classifier works in machine learning
- Building Gaussian Naive Bayes Classifier in Python
- 6 Steps to learn Naive Bayes
Neural Networks
- Introduction to Neural Networks video series
- Neural Networks Demystified video series by Welch Labs
- Neural Network playground by Google
- Implementing Neural Networks from Scratch inPython by ODSC
- Yet another introduction to Neural Network by ODSC
Support Vector Mahines
- SVM tutorial
- Why use SVM? by yHat
- SVM tutorial theory
PCA (Principle Component Analysis)
- scikit-learn PCA documentation
- PCA Tutorial by Algobeans.com
- Tutorial by ODSC
- Interpretation of the Principal Components by Penn State University
- PCA in Python by plot.y
- Visual Explanation of PCA
- PCA explanation by Siraj Raval
- Reducing Dimensionality from Dimensionality Reduction Techniques
