Machine Learning with Python
This project contains course materials presented in IUT - Fall 2017
Authors:
Materials
This course is divided into 9 chapters. Each chapter material is in a Jupyter Notebook:
- Introduction - [Notebook] [HTML]
- Supervised Learning: Regression - [Notebook] [HTML]
- Supervised Learning: Classification - [Notebook] [HTML]
- Supervised Learning: A bit more - [Notebook] [HTML]
- Model Validation, Feature Scaling & Outlier Detection - [Notebook] [HTML]
- Unsupervised Learning: Clustering - [Notebook] [HTML]
- PCA & Feature Selection - [Notebook] [HTML]
- Text Mining - [Notebook] [HTML]
- Neural Networks & Deep Learning - [Notebook] [HTML]
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License
This course is licensed under GPLv3.