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noc20_cs42_assigment_5noc20_cs42_assigment_5
noc20_cs42_assigment_6noc20_cs42_assigment_6
noc20_cs42_assigment_7noc20_cs42_assigment_7
noc20_cs42_assigment_8noc20_cs42_assigment_8
noc20_cs42_assigment_9noc20_cs42_assigment_9


Sl.No Chapter Name MP4 Download
1Introduction: What to Expect from AIDownload
2Introduction: History of AI from 40s - 90sDownload
3Introduction: History of AI in the 90sDownload
4Introduction: History of AI in NASA & DARPA(2000s)Download
5Introduction: The Present State of AIDownload
6Introduction: Definition of AI Dictionary MeaningDownload
7Introduction: Definition of AI Thinking VS Acting and Humanly VS RationallyDownload
8Introduction: Definition of AI Rational Agent View of AIDownload
9Introduction: Examples Tasks, Phases of AI & Course PlanDownload
10Uniform Search: Notion of a StateDownload
11Uniformed Search: Search Problem and Examples Part-2Download
12Uniformed Search: Basic Search Strategies Part-3Download
13Uniformed Search: Iterative Deepening DFS Part-4Download
14Uniformed Search: Bidirectional Search Part-5Download
15Informed Search: Best First Search Part-1Download
16Informed Search: Greedy Best First Search and A* Search Part-2Download
17Informed Search: Analysis of A* Algorithm Part-3Download
18Informed Search Proof of optimality of A* Part-4Download
19Informed Search: Iterative Deepening A* and Depth First Branch & Bound Part-5Download
20Informed Search: Admissible Heuristics and Domain Relaxation Part-6Download
21Informed Search: Pattern Database Heuristics Part-7Download
22Local Search: Satisfaction Vs Optimization Part-1Download
23Local Search: The Example of N-Queens Part-2Download
24Local Search: Hill Climbing Part-3Download
25Local Search: Drawbacks of Hill Climbing Part-4Download
26Local Search: of Hill Climbing With random Walk & Random Restart Part-5Download
27Local Search: Hill Climbing With Simulated Anealing Part-6Download
28Local Search: Local Beam Search and Genetic Algorithms Part-7Download
29Adversarial Search : Minimax Algorithm for two player gamesDownload
30Adversarial Search : An Example of Minimax SearchDownload
31Adversarial Search : Alpha Beta PruningDownload
32Adversarial Search : Analysis of Alpha Beta PruningDownload
33Adversarial Search : Analysis of Alpha Beta Pruning (contd...)Download
34Adversarial Search : Horizon Effect, Game Databases & Other IdeasDownload
35Adversarial Search: Summary and Other GamesDownload
36Constraint Satisfaction Problems: Representation of the atomic stateDownload
37Constraint Satisfaction Problems: Map coloring and other examples of CSPDownload
38Constraint Satisfaction Problems: Backtracking SearchDownload
39Constraint Satisfaction Problems: Variable and Value Ordering in Backtracking SearchDownload
40Constraint Satisfaction Problems: Inference for detecting failures earlyDownload
41Constraint Satisfaction Problems: Exploiting problem structureDownload
42Logic in AI : Different Knowledge Representation systems - Part 1Download
43Logic in AI : Syntax - Part - 2Download
44Logic in AI : Semantics - Part - 3Download
45Logic in AI : Forward Chaining - Part 4Download
46Logic in AI : Resolution - Part - 5Download
47Logic in AI : Reduction to Satisfiability Problems - Part - 6Download
48Logic in AI : SAT Solvers : DPLL Algorithm - Part - 7Download
49Logic in AI : Sat Solvers: WalkSAT Algorithm - Part - 8Download
50Uncertainty in AI: MotivationDownload
51Uncertainty in AI: Basics of ProbabilityDownload
52Uncertainty in AI: Conditional Independence & Bayes RuleDownload
53Bayesian Networks: SyntaxDownload
54Bayesian Networks: FactoriziationDownload
55Bayesian Networks: Conditional Independences and d-SeparationDownload
56Bayesian Networks: Inference using Variable EliminationDownload
57Bayesian Networks: Reducing 3-SAT to Bayes NetDownload
58Bayesian Networks: Rejection SamplingDownload
59Bayesian Networks: Likelihood WeightingDownload
60Bayesian Networks: MCMC with Gibbs SamplingDownload
61Bayesian Networks: Maximum Likelihood Learning"Download
62Bayesian Networks: Maximum a-Posteriori Learning Download
63Bayesian Networks: Bayesian LearningDownload
64Bayesian Networks: Structure Learning and Expectation MaximizationDownload
65Introduction, Part 10: Agents and EnvironmentsDownload
66Decision Theory: Steps in Decision TheoryDownload
67Decision Theory: Non Deterministic Uncertainty Download
68Probabilistic Uncertainty & Value of perfect informationDownload
69Expected Utility vs Expected ValueDownload
70Markov Decision Processes: DefinitionDownload
71Markov Decision Processes: An example of a PolicyDownload
72Markov Decision Processes: Policy Evaluation using system of linear equationsDownload
73Markov Decision Processes: Iterative Policy EvaluationDownload
74Markov Decision Processes: Value IterationDownload
75Markov Decision Processes: Policy Iteration and Applications & Extensions of MDPsDownload
76Reinforcement Learning: BackgroundDownload
77Reinforcement Learning: Model-based Learning for policy evaluation (Passive Learning)Download
78Reinforcement Learning: Model-free Learning for policy evaluation (Passive Learning)Download
79Reinforcement Learning: TD LearningDownload
80Reinforcement Learning: TD Learning and Computational NeuroscienceDownload
81Reinforcement Learning: Q LearningDownload
82Reinforcement Learning: Exploration vs Exploitation TradeoffDownload
83Reinforcement Learning: Generalization in RLDownload
84Deep Learning : Perceptrons and Activation functionsDownload
85Deep Learning : Example of Handwritten digit recognitionDownload
86Deep Learning : Neural Layer as matrix operationsDownload
87Deep Learning : Differentiable loss functionDownload
88Deep Learning : Backpropagation through a computational graphDownload
89Deep Learning : Thin Deep Vs Fat Shallow NetworksDownload
90Deep Learning : Convolutional Neural NetworksDownload
91Deep Learning : Deep Reinforcement LearningDownload
92Ethics of AI : Humans vs RobotsDownload
93Ethics of AI : Robustness and Transparency of AI systemsDownload
94Ethics of AI : Data Bias and Fairness of AI systemsDownload
95Ethics of AI : Accountability, privacy and Human-AI interactionDownload
96WrapupDownload

Sl.No Chapter Name English
1Introduction: What to Expect from AIDownload
Verified
2Introduction: History of AI from 40s - 90sDownload
Verified
3Introduction: History of AI in the 90sDownload
Verified
4Introduction: History of AI in NASA & DARPA(2000s)Download
Verified
5Introduction: The Present State of AIDownload
Verified
6Introduction: Definition of AI Dictionary MeaningDownload
Verified
7Introduction: Definition of AI Thinking VS Acting and Humanly VS RationallyDownload
Verified
8Introduction: Definition of AI Rational Agent View of AIDownload
Verified
9Introduction: Examples Tasks, Phases of AI & Course PlanDownload
Verified
10Uniform Search: Notion of a StateDownload
Verified
11Uniformed Search: Search Problem and Examples Part-2Download
Verified
12Uniformed Search: Basic Search Strategies Part-3Download
Verified
13Uniformed Search: Iterative Deepening DFS Part-4Download
Verified
14Uniformed Search: Bidirectional Search Part-5Download
Verified
15Informed Search: Best First Search Part-1Download
Verified
16Informed Search: Greedy Best First Search and A* Search Part-2Download
Verified
17Informed Search: Analysis of A* Algorithm Part-3Download
Verified
18Informed Search Proof of optimality of A* Part-4Download
Verified
19Informed Search: Iterative Deepening A* and Depth First Branch & Bound Part-5Download
Verified
20Informed Search: Admissible Heuristics and Domain Relaxation Part-6Download
Verified
21Informed Search: Pattern Database Heuristics Part-7Download
Verified
22Local Search: Satisfaction Vs Optimization Part-1Download
Verified
23Local Search: The Example of N-Queens Part-2Download
Verified
24Local Search: Hill Climbing Part-3Download
Verified
25Local Search: Drawbacks of Hill Climbing Part-4Download
Verified
26Local Search: of Hill Climbing With random Walk & Random Restart Part-5Download
Verified
27Local Search: Hill Climbing With Simulated Anealing Part-6Download
Verified
28Local Search: Local Beam Search and Genetic Algorithms Part-7Download
Verified
29Adversarial Search : Minimax Algorithm for two player gamesDownload
Verified
30Adversarial Search : An Example of Minimax SearchDownload
Verified
31Adversarial Search : Alpha Beta PruningDownload
Verified
32Adversarial Search : Analysis of Alpha Beta PruningDownload
Verified
33Adversarial Search : Analysis of Alpha Beta Pruning (contd...)Download
Verified
34Adversarial Search : Horizon Effect, Game Databases & Other IdeasDownload
Verified
35Adversarial Search: Summary and Other GamesDownload
Verified
36Constraint Satisfaction Problems: Representation of the atomic stateDownload
Verified
37Constraint Satisfaction Problems: Map coloring and other examples of CSPDownload
Verified
38Constraint Satisfaction Problems: Backtracking SearchDownload
Verified
39Constraint Satisfaction Problems: Variable and Value Ordering in Backtracking SearchDownload
Verified
40Constraint Satisfaction Problems: Inference for detecting failures earlyDownload
Verified
41Constraint Satisfaction Problems: Exploiting problem structureDownload
Verified
42Logic in AI : Different Knowledge Representation systems - Part 1Download
Verified
43Logic in AI : Syntax - Part - 2Download
Verified
44Logic in AI : Semantics - Part - 3Download
Verified
45Logic in AI : Forward Chaining - Part 4Download
Verified
46Logic in AI : Resolution - Part - 5Download
Verified
47Logic in AI : Reduction to Satisfiability Problems - Part - 6Download
Verified
48Logic in AI : SAT Solvers : DPLL Algorithm - Part - 7Download
Verified
49Logic in AI : Sat Solvers: WalkSAT Algorithm - Part - 8Download
Verified
50Uncertainty in AI: MotivationDownload
Verified
51Uncertainty in AI: Basics of ProbabilityDownload
Verified
52Uncertainty in AI: Conditional Independence & Bayes RuleDownload
Verified
53Bayesian Networks: SyntaxDownload
Verified
54Bayesian Networks: FactoriziationDownload
Verified
55Bayesian Networks: Conditional Independences and d-SeparationDownload
Verified
56Bayesian Networks: Inference using Variable EliminationDownload
Verified
57Bayesian Networks: Reducing 3-SAT to Bayes NetDownload
Verified
58Bayesian Networks: Rejection SamplingDownload
Verified
59Bayesian Networks: Likelihood WeightingDownload
Verified
60Bayesian Networks: MCMC with Gibbs SamplingDownload
Verified
61Bayesian Networks: Maximum Likelihood Learning"Download
Verified
62Bayesian Networks: Maximum a-Posteriori Learning Download
Verified
63Bayesian Networks: Bayesian LearningDownload
Verified
64Bayesian Networks: Structure Learning and Expectation MaximizationDownload
Verified
65Introduction, Part 10: Agents and EnvironmentsDownload
Verified
66Decision Theory: Steps in Decision TheoryDownload
Verified
67Decision Theory: Non Deterministic Uncertainty Download
Verified
68Probabilistic Uncertainty & Value of perfect informationDownload
Verified
69Expected Utility vs Expected ValueDownload
Verified
70Markov Decision Processes: DefinitionDownload
Verified
71Markov Decision Processes: An example of a PolicyDownload
Verified
72Markov Decision Processes: Policy Evaluation using system of linear equationsDownload
Verified
73Markov Decision Processes: Iterative Policy EvaluationDownload
Verified
74Markov Decision Processes: Value IterationDownload
Verified
75Markov Decision Processes: Policy Iteration and Applications & Extensions of MDPsDownload
Verified
76Reinforcement Learning: BackgroundDownload
Verified
77Reinforcement Learning: Model-based Learning for policy evaluation (Passive Learning)Download
Verified
78Reinforcement Learning: Model-free Learning for policy evaluation (Passive Learning)Download
Verified
79Reinforcement Learning: TD LearningDownload
Verified
80Reinforcement Learning: TD Learning and Computational NeuroscienceDownload
Verified
81Reinforcement Learning: Q LearningDownload
Verified
82Reinforcement Learning: Exploration vs Exploitation TradeoffDownload
Verified
83Reinforcement Learning: Generalization in RLDownload
Verified
84Deep Learning : Perceptrons and Activation functionsDownload
Verified
85Deep Learning : Example of Handwritten digit recognitionDownload
Verified
86Deep Learning : Neural Layer as matrix operationsDownload
Verified
87Deep Learning : Differentiable loss functionDownload
Verified
88Deep Learning : Backpropagation through a computational graphDownload
Verified
89Deep Learning : Thin Deep Vs Fat Shallow NetworksDownload
Verified
90Deep Learning : Convolutional Neural NetworksDownload
Verified
91Deep Learning : Deep Reinforcement LearningDownload
Verified
92Ethics of AI : Humans vs RobotsDownload
Verified
93Ethics of AI : Robustness and Transparency of AI systemsDownload
Verified
94Ethics of AI : Data Bias and Fairness of AI systemsDownload
Verified
95Ethics of AI : Accountability, privacy and Human-AI interactionDownload
Verified
96WrapupDownload
Verified


Sl.No Language Book link
1EnglishDownload
2BengaliNot Available
3GujaratiNot Available
4HindiNot Available
5KannadaNot Available
6MalayalamNot Available
7MarathiNot Available
8TamilNot Available
9TeluguNot Available