Index
Statistics and Machine Learning in Python
Navigation
Python ecosystem for data-science
Introduction to Machine Learning
Data analysis methodology
Import libraries
Basic operations
Data types
Execution control statements
List comprehensions, iterators, etc.
Functions
Regular expression
System programming
Scripts and argument parsing
Networking
Modules and packages
Object Oriented Programming (OOP)
Style guide for Python programming
Documenting
Exercises
Numpy: arrays and matrices
Pandas: data manipulation
Data visualization: matplotlib & seaborn
Univariate statistics
Lab: Brain volumes study
Linear Mixed Models
Multivariate statistics
Time series in python
Linear dimension reduction and feature extraction
Manifold learning: non-linear dimension reduction
Clustering
Linear models for regression problems
Linear models for classification problems
Non-linear models
Resampling methods
Ensemble learning: bagging, boosting and stacking
Gradient descent
Lab: Faces recognition using various learning models
Backpropagation
Multilayer Perceptron (MLP)
Convolutional neural network
Transfer Learning Tutorial
Related Topics
Documentation overview
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