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