Machine-Learning-Content

Topics :

Mathematics

Linear Algebra
Differential Calculas
Probability and Statistics
Numerical Methods and Optimisation

Python

Basic Constructs
Object Oriented Programming
Pythonic way
Numpy, Pandas and Matplotlib
Scikitlearn
Tensorflow and keras

Machine Learning

Linear Regression
Logistic Regression
Support Vector Machines
Principal Component Analysis
Clustering and Unsupervised Learning
Bias and Variance

Deep Learning Basics

Artificial Neural Networks
Optimisation 
Regularisation

Computer Vision

Convolutional Neural Networks
Image Classification
Object Detection
Face Recogntion

Sequential Networks and NLP

Recurrent Neural Networks
Time Series
Long short term memory
BERT

Generative Adversarial Networks

Autoencoders

References:

Deep Learning Book - Ian Goodfellow https://amzn.to/3l5pPh3

Hands on ML with scikit learn and Tensorflow 2.0 - Aurélien Géron https://amzn.to/2EhcFgd