Machine Learning Tutorials for Python

Machine learning means letting a program learn from data instead of writing the rules by hand. You give it examples, it finds the pattern, and it uses that pattern to predict something new.

Python is the usual language for this, because the libraries are all there. These are the machine learning articles on the site. If you have never done machine learning before, start at the top and work down.

Reading about it is one thing, writing it is another. Try the exercises on PyChallenge and you get instant feedback on every line.

Machine learning

• How do I learn Machine Learning?
• Machine Learning
• Machine Learning Tasks
• The importance of unsupervised learning
• What is supervised learning?
• What is the difference between supervised and unsupervised learning?
• What is the difference between statistics and Machine Learning?
• Machine Learning Classifier
• What are the Advantages of Different Classification Algorithms
• Training and test data
• bag of words
• bag of words euclidian distance

Decision Tree

• What are the Advantages of Using a Decision Tree for Classification?
• Decision tree
• Decision tree visual example

K-means

• k Nearest Neighbors
• kmeans clustering algorithm
• How is the k-nearest neighbor algorithm different from k-means cl
• kmeans clustering centroi
• kmeans elbow method
• kmeans text clustering

Regression

• Linear Regression
• logistic regression spam filter

Applications

• Translate
• Speech Recognition
• Text to speech
• Extract text from image

Algorithms

• Naive Bayes classifier
• Support Vector Machine
• Random Forest
• Neuroevolution

Boosting

• AdaBoost
• Random Forest
• Gradient Boosting

General

• Top Data Mining Algorithms
• Is There a Recommended Package for Machine Learning in Python?

If you want to try this yourself, the exercises on PyChallenge turn the same idea into a few short problems with instant feedback.