AI ML

Descriptive Statistics · Probability Theory · Probability Distributions · Sampling and Experimental Design · Inferential Statistics · Statistical Modeling · Time Series Analysis

Problem Types · Model Families · Core Algorithms · Multi-Class And Multi-Label Strategies · Ensemble Methods · Model Development · Model Evaluation · Imbalanced And Cost-Sensitive Learning · Interpretability And Explainability

Problem Types · Clustering Algorithms · Dimensionality Reduction · Density Estimation · Anomaly Detection · Association Rule Learning · Representation Learning · Model Development · Evaluation

Neural Network Basics · Activation Functions · Weight Initialization · Backpropagation · Optimizers · Regularization & Normalization · Convolutional Networks · Recurrent Networks (RNN/LSTM) · Transformer (Foundations)

RL Paradigms · Exploration vs Exploitation · Multi-Armed Bandits · Tabular Methods · Function Approximation · Deep Reinforcement Learning · Model-Based RL · Reward Engineering & Imitation · Extensions & Variants · RL Frameworks & Environments · Applications