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Udemy - Artificial Intelligence I: Basics and Games in Java - [PaidCoursesForFree]

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Udemy - Artificial Intelligence I: Basics and Games in Java - [PaidCoursesForFree] (Size: 1.24 GB)
  1. Introduction
  1. Introduction.mp4 3.55 MB
  1. Introduction.vtt 1.94 KB
  2. What is AI good for.mp4 10.32 MB
  2. What is AI good for.vtt 5.48 KB
  10. Tic-Tac-Toe Game
  1. About the game.mp4 6.83 MB
  1. About the game.vtt 3.44 KB
  10. Running tic-tac-toe.mp4 8.43 MB
  10. Running tic-tac-toe.vtt 5.29 KB
  2. Cell.mp4 8.15 MB
  2. Cell.vtt 3.83 KB
  3. Constants and Player.mp4 6.36 MB
  3. Constants and Player.vtt 3.15 KB
  4. Game implementation I.mp4 18.55 MB
  4. Game implementation I.vtt 8.12 KB
  5. Game implementation II.mp4 9.66 MB
  5. Game implementation II.vtt 3.67 KB
  6. Board implementation I.mp4 16.48 MB
  6. Board implementation I.vtt 6.9 KB
  7. Board implementationj II - isWinning().mp4 9.04 MB
  7. Board implementationj II - isWinning().vtt 3.54 KB
  8. Board implementation III.mp4 16.53 MB
  8. Board implementation III.vtt 5.87 KB
  9. Minimax algorithm.mp4 21.28 MB
  9. Minimax algorithm.vtt 9.06 KB
  11. Course Materials (DOWNLOADS)
  1. Course materials.html 60 B
  1.1 AI_Udemy.zip.zip 9.42 MB
  12. DISCOUNT FOR OTHER COURSES!
  1. 90% OFF For Other Courses.html 5.05 KB
  2. Graph-Search Algorithms (Path Finding Algorithms)
  1. Why to consider graph algorithms.mp4 3.7 MB
  1. Why to consider graph algorithms.vtt 1.82 KB
  10. A search illustration.mp4 15.82 MB
  10. A search illustration.vtt 9.42 KB
  11. A search implementation I.mp4 52.94 MB
  11. A search implementation I.vtt 8.18 KB
  12. A search implementation II.mp4 68.21 MB
  12. A search implementation II.vtt 7.73 KB
  13. Path finding algorithms comparison.mp4 6.13 MB
  13. Path finding algorithms comparison.vtt 2.8 KB
  2. Breadth-first search introduction.mp4 20.75 MB
  2. Breadth-first search introduction.vtt 10.76 KB
  3. Breadt-first search implementation.mp4 24.43 MB
  3. Breadt-first search implementation.vtt 12.18 KB
  4. Depth-first search introduction.mp4 22.15 MB
  4. Depth-first search introduction.vtt 12.16 KB
  5. Depth-first search implementation I - with stack.mp4 22.94 MB
  5. Depth-first search implementation I - with stack.vtt 10.41 KB
  6. Depth-first search implementation II - with recursion.mp4 8.36 MB
  6. Depth-first search implementation II - with recursion.vtt 4.33 KB
  7. Enhanced search algorithms introduction.mp4 8.95 MB
  7. Enhanced search algorithms introduction.vtt 4.53 KB
  8. Iterative deepening depth-first search (IDDFS).mp4 21.43 MB
  8. Iterative deepening depth-first search (IDDFS).vtt 9.92 KB
  9. A search introduction.mp4 17.25 MB
  9. A search introduction.vtt 8.24 KB
  3. Basic Search Optimization Algorithms
  1. Brute-force search introduction.mp4 9.24 MB
  1. Brute-force search introduction.vtt 5.13 KB
  2. Brute-force search example.mp4 17.86 MB
  2. Brute-force search example.vtt 8.89 KB
  3. Stochastic search introduction.mp4 9.28 MB
  3. Stochastic search introduction.vtt 5.12 KB
  4. Stochastic search example.mp4 15.53 MB
  4. Stochastic search example.vtt 7.81 KB
  5. Hill climbing introduction.mp4 7.38 MB
  5. Hill climbing introduction.vtt 4 KB
  6. Hill climbing example.mp4 15.37 MB
  6. Hill climbing example.vtt 7.26 KB
  4. Meta-Heuristic Optimization Methods
  1. Heuristics VS meta-heuristics.mp4 16.59 MB
  1. Heuristics VS meta-heuristics.vtt 9.1 KB
  5. Tabu Search
  1. Tabu search introduction - basics.mp4 27.07 MB
  1. Tabu search introduction - basics.vtt 6.3 KB
  2. Tabu search introduction - tabu tenure.mp4 26.35 MB
  2. Tabu search introduction - tabu tenure.vtt 6.11 KB
  3. Tabu search illustration.mp4 19.57 MB
  3. Tabu search illustration.vtt 5.87 KB
  4. Tabu search implementation I.mp4 52.27 MB
  4. Tabu search implementation I.vtt 52.27 MB
  5. Tabu search implementation II.mp4 78.34 MB
  5. Tabu search implementation II.vtt 9.47 KB
  6. Simulated Annealing
  1. Simulated annealing introduction.mp4 23.67 MB
  1. Simulated annealing introduction.vtt 11.87 KB
  2. Simulated annealing - function extremum I.mp4 7.27 MB
  2. Simulated annealing - function extremum I.vtt 3.61 KB
  3. Simulated annealing - function extremum II.mp4 22.74 MB
  3. Simulated annealing - function extremum II.vtt 11.25 KB
  4. Simulated annealing - function extremum III.mp4 9.36 MB
  4. Simulated annealing - function extremum III.vtt 4.95 KB
  5. Travelling salesman problem I - city.mp4 21.94 MB
  5. Travelling salesman problem I - city.vtt 9.97 KB
  6. Travelling salesman problem II - tour.mp4 29.88 MB
  6. Travelling salesman problem II - tour.vtt 13 KB
  7. Travelling salesman problem III - annealing algorithm.mp4 23.02 MB
  7. Travelling salesman problem III - annealing algorithm.vtt 10.2 KB
  8. Travelling salesman problem IV - testing.mp4 9.26 MB
  8. Travelling salesman problem IV - testing.vtt 5 KB
  7. Genetic Algorithms
  1. Genetic algorithms introduction - basics.mp4 9.89 MB
  1. Genetic algorithms introduction - basics.vtt 5.16 KB
  10. Genetic algorithm implementation V - function optimum.mp4 24.98 MB
  10. Genetic algorithm implementation V - function optimum.vtt 10.64 KB
  2. Genetic algorithms introduction - chromosomes.mp4 5.38 MB
  2. Genetic algorithms introduction - chromosomes.vtt 2.81 KB
  3. Genetic algorithms introduction - crossover.mp4 7.43 MB
  3. Genetic algorithms introduction - crossover.vtt 3.99 KB
  4. Genetic algorithms introduction - mutation.mp4 6.92 MB
  4. Genetic algorithms introduction - mutation.vtt 3.48 KB
  5. Genetic algorithms introduction - the algorithm.mp4 7.29 MB
  5. Genetic algorithms introduction - the algorithm.vtt 3.85 KB
  6. Genetic algorithm implementation I - individual.mp4 18.66 MB
  6. Genetic algorithm implementation I - individual.vtt 8.81 KB
  7. Genetic algorithm implementation II - population.mp4 11.68 MB
  7. Genetic algorithm implementation II - population.vtt 5.29 KB
  8. Genetic algorithm implementation III - the algorithm.mp4 20.06 MB
  8. Genetic algorithm implementation III - the algorithm.vtt 8.71 KB
  9. Genetic algorithm implementation IV - testing.mp4 16.06 MB
  9. Genetic algorithm implementation IV - testing.vtt 7.27 KB
  8. Particle Swarm Optimization
  1. Swarm intelligence intoduction.mp4 15.46 MB
  1. Swarm intelligence intoduction.vtt 7.82 KB
  2. Particle swarm optimization introduction I - basics.mp4 18.78 MB
  2. Particle swarm optimization introduction I - basics.vtt 8.79 KB
  3. Particle swarm optimization introduction II - the algorithm.mp4 24.75 MB
  3. Particle swarm optimization introduction II - the algorithm.vtt 11.99 KB
  4. Particle swarm optimization implementation I - particle.mp4 22.18 MB
  4. Particle swarm optimization implementation I - particle.vtt 10.49 KB
  5. Particle swarm optimization implementation II - initialize.mp4 15.2 MB
  5. Particle swarm optimization implementation II - initialize.vtt 6.39 KB
  6. Particle swarm optimization implementation III - the algorithm.mp4 24.25 MB
  6. Particle swarm optimization implementation III - the algorithm.vtt 9.43 KB
  7. Particle swarm optimization implementation IV - testing.mp4 10.37 MB
  7. Particle swarm optimization implementation IV - testing.vtt 4.88 KB
  9. Minimax Algorithm - Game Engines
  1. Game trees introduction.mp4 9.22 MB
  1. Game trees introduction.vtt 4.63 KB
  2. Minimax algorithm introduction - basics.mp4 9.79 MB
  2. Minimax algorithm introduction - basics.vtt 4.72 KB
  3. Minimax algorithm introduction - the algorithm.mp4 15.83 MB
  3. Minimax algorithm introduction - the algorithm.vtt 7.95 KB
  4. Minimax algorithm introduction - relation with tic-tac-toe.mp4 9.95 MB
  4. Minimax algorithm introduction - relation with tic-tac-toe.vtt 5.17 KB
  5. Alpha-beta pruning introduction.mp4 12.22 MB
  5. Alpha-beta pruning introduction.vtt 5.71 KB
  6. Alpha-beta pruning example.mp4 20.34 MB
  6. Alpha-beta pruning example.vtt 9.73 KB
  7. Chess problem.mp4 4.89 MB
  7. Chess problem.vtt 2.48 KB
  PaidCoursesForFree.com.url 121 B

Description




A guide how to create smart applications, AI, genetic algorithms, pruning, heuristics and metaheuristics

What you’ll learn
* Get a good grasp of artificial intelligence
* Understand how AI algorithms work
* Able to create AI algorithms on your own from scratch
* Understand meta-heuristics

Requirements
* Basic Java (SE)
* Some basic algorithms ( maximum/minimum finding )
* Basic math ( functions )

Description
This course is about the fundamental concepts of artificial intelligence. This topic is getting very hot nowadays because these learning algorithms can be used in several fields from software engineering to investment banking. Learning algorithms can recognize patterns which can help detecting cancer for example. We may construct algorithms that can have a very good guess about stock price movement in the market.

Section 1:
* path findinf algorithms
* graph traversal (BFS and DFS)
* enhanced search algorihtms
* A* search algorithm

Section 2:
* basic optimization algorithms
* brute-force search
* stochastic search and hill climbing algorithm

Section 3:
* heuristics and meta-heuristics
* tabu search
* simulated annealing
* genetic algorithms
* particle swarm optimization

Section 4:
* minimax algorithm
* game trees
* applications of game trees in chess
* tic tac toe game and its implementation

In the first chapter we are going to talk about the basic graph algorithms. Several advanced algorithms can be solved with the help of graphs, so as far as I am concerned these algorithms are the first steps.

Second chapter is about local search: finding minimum and maximum or global optimum in the main. These searches are used frequently when we use regression for example and want to find the parameters for the fit. We will consider basic concepts as well as the more advanced algorithms: heuristics and meta-heuristics.

The last topic will be about minimax algorithm and how to use this technique in games such as chess or tic-tac-toe, how to build and construct a game tree, how to analyze these kinds of tree like structures and so on. We will implement the tic-tac-toe game together in the end.

Thanks for joining the course, let’s get started!

Who this course is for:
* This course is meant for students or anyone who interested in programming and have some background in basic Java

Source: PaidCoursesForFree.com

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