Introduction
Machine learning is a branch of artificial intelligence that enables machines to learn from data and perform tasks without explicit instructions. Machine learning algorithms can analyze large amounts of data, find patterns, and make predictions or classifications based on the data. Machine learning can be used for various applications, such as product recommendation, fraud detection, speech recognition, self-driving cars, and more. The four main types of machine learning are supervised, unsupervised, semi-supervised, and reinforcement learning.
Contents
Theory of Machine Learning
Machine Learning Problems
Feasibility of Learning
Model Complexity: VC Dimension
Fitting
Benign Overfitting
Machine Learning Models
Linear Regression
Logistic Regression
Support Vector Machine
K-means Clustering
Decision Tree
Deep Learning and Neural Networks
Reinforcement Learning
Physics Informed Neural Networks