The book for the course: "Machine Learning in Action, ISBN 9781617290183"
The book contains a few errors in the code examples, there are updated versions of the examples on the books GitHub page.: https://github.com/pbharrin/machinelearninginaction
Reading: Chapter 1 + 2
Subjects:
* PyCharm
* Python (Syntax, operators, OOP (Linked List), NumPy)
* Supervised (kNN)
Preparation:
* Read chapters, install pycharm, install python 2.7
Reading: Chapter 3 + 4
Subjects:
* Supervised (DT, Naive Bayes)
* Cleaning Datasets
Preparation:
* Read chapters
Reading: Chapter 10 + 11 + 12
Subjects:
* Unsupervised (FP-Tree, Apriori)
Preparation:
* Read chapters
Reading: ???
Subjects:
* Neural Network
* Which algorithm and how to approach a problem.
Preparation:
* ???