The Art of Intelligence

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160 videos

Welcome to "The Art of Intelligence"! I’m an Associate Professor specializing in Artificial Intelligence, and this channel is designed to be your comprehensi...

Latest Videos

ML10_ Deep Q-Network (DQN) From Q-Learning to Deep Reinforcement Learning

ML09_ Deep Reinforcement Learning (DRL) Foundations, Algorithms, and Real-World Applications

DM14_ Graph Theory Explained Foundations, Algorithms, and Classic Problems Discrete Mathematics

LA14_ Singular Value Decomposition (SVD) Explained Concepts, Computation, and Applications

DM13_ Discrete Probability — Foundations, Events, Random Variables, and Key Theorems

LA13_ Matrix Factorization in Linear Algebra QR, LU, Spectral Decomposition & Orthogonality

ML08_ Natural Language Processing (NLP) Explained A Complete Lecture in the Machine Learning Series

ML07_ Reinforcement Learning Explained From Foundations to Advanced Concepts

RT08_ Manuscript Submission Process A Complete Guide for Research Methodology & Technical Writing

DM12_ Permutation & Combination Explained Discrete Mathematics Lecture (Binomial Theorem Included)

DM11_ Counting in Discrete Mathematics Fundamental Principles, Rules, and Applications

LA12_ Orthogonality in Linear Algebra Norm, Distance, Dot Product, Projections, and Least Squares

ML04_ Linear Regression for Used Car Price Prediction in Python & Google Colab

ML06_ Clustering in Machine Learning Principles, Methods, and Key Algorithms

ML05_ Backpropagation Mathematical Foundations and Training Dynamics in Neural Networks

RT07_ Publication Venues in Research Journals, Conferences, Rankings, and Metrics Explained

DM10_ Induction and Recursion Discrete Mathematics Lecture Series

LA11_ Diagonalization in Linear Algebra Eigenvalues, Eigenspaces & Diagonalizable Matrices

ML04_ Artificial Neural Networks Foundations, Learning Algorithms & Applications

DM09_ Number Theory in Discrete Mathematics Divisibility, Congruences, Bases & GCDLCM Explained

LA10_ Eigenvalues & Eigenvectors Theory, Geometry, and Applications Linear Algebra Lecture

RT06_ Plagiarism in Scholarly Publishing Ethics, Regulations, and Best Practices

LA09_ Vector Subspaces, Null Space, Basis, and Dimension — A Complete Linear Algebra Guide

RT06_ Plagiarism in Scholarly Publishing Ethics, Regulations, and Best Practices

ML03_ Linear Regression in Machine Learning Concepts, Mathematics, Gradient Descent

DM08_ Algorithms in Discrete Mathematics From Pseudocode to Time Complexity

LA09_ Vector Subspaces, Null Space, Basis, and Dimension — A Complete Linear Algebra Guide

ML01_ Overview of Machine Learning Foundations, Frameworks, and Real-World Applications

DM07_ Matrices Discrete Mathematics Lecture Types, Operations, Boolean Matrices & Applications

LA08_ Determinant Linear Algebra Lecture Series Properties, Cofactor Expansion & Cramer’s Rule