Introduction to Python for Data Sciences

The course material is fully derived from a fork of Franck Iutzeler's class at UGA. He and I are both greatly indebted to many people and resources for this course:

Alexandre Gramfort for his kind permission tu use some material from his course at Telecom Paris and his scikit-learn tutorial at SciPy 2016.
Adeline Leclerc Samson for giving me the opportunity of teaching this course.
Anatoli Juditski for his advice and the conception of the Operation research course.
The Python Data Science Handbook by Jake VanderPlas, see on GitHub.
Many users feedbacks.
the various docs and examples on the websites of Numpy, Scipy, CvxOpt, Pandas, Scikit Learn, TensorFlow
Franck Iutzeler himself for passing all this content to me and his advices regarding the pedagogical aspects of the course.

floffy-f/Introduction-to-Python-for-Data-Sciences

Introduction to Python for Data Sciences

Outline

Chap. 1 - Introduction to Python

Chap. 2 - Python for Scientific Computing

Chap. 3 - Data Handling with Pandas

Chap. 4 - Machine Learning with ScikitLearn

Projects

Math-leaning projects

Project 1: Optimization ↪

Project 2: MCMC 🪙

Learning-leaning projects

Project 3: Text 📚

Project 4: Images 🖼

Data-leaning projects

Project 5: Scientific data 🐼

Credits