Scikit-learn : Machine Learning Simplified

If you are a programmer and want to explore machine learning and data-based methods to build intelligent applications and enhance your programming skills, this is the course for you. No previous experience with machine-learning algorithms is required.

What You Will Learn
Review fundamental concepts including supervised and unsupervised experiences, common tasks, and performance metrics
Classify objects (from documents to human faces and flower species) based on some of their features, using a variety of methods from Support Vector Machines to Naïve Bayes
Use Decision Trees to explain the main causes of certain phenomena such as passenger survival on the Titanic
Evaluate the performance of machine learning systems in common tasks
Master algorithms of various levels of complexity and learn how to analyze data at the same time
Learn just enough math to think about the connections between various algorithms
Customize machine learning algorithms to fit your problem, and learn how to modify them when the situation calls for it
Incorporate other packages from the Python ecosystem to munge and visualize your dataset
Improve the way you build your models using parallelization techniques