Archives
Unsupervised Learning; 𝑲-Means Clustering; Principal Component Analysis (PCA); Autoencoders – Part 1
Introduction: Machine Learning (ML) & Artificial Intelligence (AI); Definitions of Datasets; Discriminative & Generative AI Models; Supervised Learning, Linear & Logistic Regression – Part 2
Introduction: Machine Learning (ML) & Artificial Intelligence (AI); Definitions of Datasets; Discriminative & Generative AI Models; Supervised Learning, Linear & Logistic Regression – Part 1
Metropolis-Hastings Algorithm; Gibbs Sampling;Markov Random Fields, Ising Model, Simulated Annealing – Part 2
Metropolis-Hastings Algorithm; Gibbs Sampling;Markov Random Fields, Ising Model, Simulated Annealing – Part 1
Restrictive Boltzmann Machine (RBM); Contrastive Divergence Algorithm; Deep Belief Networks (DBN)
Reinforcement Learning – Dynamic Programming
1. Markov Decision Processes
2. Bellman’s Optimality Criterion
3. Policy Iteration Algorithm
4. Value Iteration Algorithm
Model-Free Methods in Reinforcement Learning:Direct Approximations, Random Trajectories & State-Action Counting, Temporal-Difference & Stochastic Q-Learning; Distributed Multi-Agent Reinforcement Learning; Bellman-Ford Algorithm, BGP Routing in the Internet
Binary Classification – Kernel Methods: Separability of Patterns, Cover’s Theorem; Radial-Basis Function (RBF) Networks; RBF Hybrid Learning; Support Vector Machines (SVM)
1. Non-Parametric Classifiers, K-Nearest Neighbors – KNN; 2. Statistical Evaluation of Binary Classification: Confusion Matrix, ROC, AUC; 3. Parametric Probabilistic Classification: MLE & MAP Estimation, Bayes & Naive Bayes Classifiers
Decision Trees
1. Classification And Regression Trees (CART)
2. Gini Index, 2. Random Forests
3. Bagging (Bootstrap & aggregating) Algorithms
eXplainable AI (XAI)
1. Definitions, Intrinsic & Model-Agnostic XAI Methods
2. PI (Permutation Feature Importance)
3. SHAP (Shapley Additive exPlanations)
4. LIME (Local Interpretable Model Agnostic Explanation)
Recurrent Neural Networks (RNN)
1. Memory Models
2. Hopfield Recurrent Networks
3. Long Short-Term Memory (LSTM) Networks; Large Language Models (LLM)