Uniform Search: Notion of a State

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Uniformed Search: Search Problem and Examples Part-2

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Uniformed Search: Basic Search Strategies Part-3

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Uniformed Search: Iterative Deepening DFS Part-4

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Uniformed Search: Bidirectional Search Part-5

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Informed Search: Greedy Best First Search and A* Search Part-2

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Informed Search: Best First Search Part-1

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Informed Search: Greedy Best First Search and A* Search Part-2

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Informed Search: Analysis of A* Algorithm Part-3

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Informed Search Proof of optimality of A* Part-4

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Informed Search: Iterative Deepening A* and Depth First Branch & Bound Part-5

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Informed Search: Admissible Heuristics and Domain Relaxation Part-6

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Informed Search: Pattern Database Heuristics Part-7

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Local Search: Satisfaction Vs Optimization Part-1

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Local Search: The Example of N-Queens Part-2

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Local Search: Hill Climbing Part-3

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Local Search: Drawbacks of Hill Climbing Part-4

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Local Search: of Hill Climbing With random Walk & Random Restart Part-5

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Local Search: Hill Climbing With Simulated Anealing Part-6

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Local Search: Local Beam Search and Genetic Algorithms Part-7

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Adversarial Search : Minimax Algorithm for two player games

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Adversarial Search : An Example of Minimax Search

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Adversarial Search : Alpha Beta Pruning

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Adversarial Search : Analysis of Alpha Beta Pruning

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Adversarial Search : Analysis of Alpha Beta Pruning (contd...)

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Adversarial Search : Horizon Effect, Game Databases & Other Ideas

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Adversarial Search: Summary and Other Games

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Constraint Satisfaction Problems: Representation of the atomic state

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Constraint Satisfaction Problems: Map coloring and other examples of CSP

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Constraint Satisfaction Problems: Backtracking Search

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Constraint Satisfaction Problems: Variable and Value Ordering in Backtracking Search

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Constraint Satisfaction Problems: Inference for detecting failures early

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Constraint Satisfaction Problems: Exploiting problem structure

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Logic in AI : Different Knowledge Representation systems - Part 1

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Logic in AI : Syntax - Part - 2

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Logic in AI : Semantics - Part - 3

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Logic in AI : Forward Chaining - Part 4

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Logic in AI : Resolution - Part - 5

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Logic in AI : Reduction to Satisfiability Problems - Part - 6

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Logic in AI : SAT Solvers : DPLL Algorithm - Part - 7

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Logic in AI : Sat Solvers: WalkSAT Algorithm - Part - 8

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Uncertainty in AI: Motivation

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Uncertainty in AI: Basics of Probability

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Uncertainty in AI: Conditional Independence & Bayes Rule

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Bayesian Networks: Syntax

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Bayesian Networks: Factoriziation

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Bayesian Networks: Conditional Independences and d-Separation

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Bayesian Networks: Inference using Variable Elimination

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Bayesian Networks: Reducing 3-SAT to Bayes Net

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Bayesian Networks: Rejection Sampling

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Bayesian Networks: Likelihood Weighting

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Bayesian Networks: MCMC with Gibbs Sampling

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Bayesian Networks: Maximum Likelihood Learning

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Bayesian Networks: Maximum a-Posteriori LearningÂ

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Bayesian Networks: Bayesian Learning

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Bayesian Networks: Structure Learning and Expectation Maximization

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Introduction, Part 10: Agents and Environments

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Decision Theory: Steps in Decision Theory

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Decision Theory: Non Deterministic Uncertainty

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Probabilistic Uncertainty & Value of perfect information

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Expected Utility vs Expected Value

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Markov Decision Processes: Definition

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Markov Decision Processes: An example of a Policy

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Markov Decision Processes: Policy Evaluation using system of linear equations

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Markov Decision Processes: Iterative Policy Evaluation

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Markov Decision Processes: Value Iteration

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Markov Decision Processes: Policy Iteration and Applications & Extensions of MDPs

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Reinforcement Learning: Background

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Reinforcement Learning: Model-based Learning for policy evaluation (Passive Learning)

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Reinforcement Learning: Model-free Learning for policy evaluation (Passive Learning)

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Reinforcement Learning: TD Learning

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Reinforcement Learning: TD Learning and Computational Neuroscience

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Reinforcement Learning: Q Learning

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Reinforcement Learning: Exploration vs Exploitation Tradeoff

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Reinforcement Learning: Generalization in RL

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Deep Learning : Perceptrons and Activation functions

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Deep Learning : Example of Handwritten digit recognition

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Deep Learning : Neural Layer as matrix operations

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Deep Learning : Differentiable loss function

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Deep Learning : Backpropagation through a computational graph

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Deep Learning : Thin Deep Vs Fat Shallow Networks

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Deep Learning : Convolutional Neural Networks

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Ethics of AI : Humans vs Robots

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Ethics of AI : Robustness and Transparency of AI systems

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Ethics of AI : Data Bias and Fairness of AI systems

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Ethics of AI : Accountability, privacy and Human-AI interaction

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Wrapup

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