Published on: 2022-12-22 05:59:50
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AI and Meta-Heuristics (Combinatorial Optimization) Python published by Udemy Academy. Graph algorithms, genetic algorithms, simulated annealing, swarm intelligence, discovery, minimax and meta-heuristics.
This course is about the fundamental concepts of artificial intelligence and meta-heuristics with Python. This topic is very hot nowadays because these learning algorithms can be used in several fields from software engineering to investment banking. Learning algorithms can recognize patterns that can help diagnose cancer, for example. We may build algorithms that make very good guesses about the movement of stock prices in the market. In the first chapters we are going to talk about basic graph algorithms – breadth first search (BFS), depth first search (DFS) and A* search algorithms. Several advanced algorithms can be solved with the help of graphs, so I think these algorithms are very important. The next chapters are about heuristics and meta-heuristics. We will consider the theory as well as the implementation of simulated annealing, genetic algorithms and particle swarm optimization – with several problems such as the famous N queen problem, the traveling salesman problem (TSP), etc.
No programming experience needed. You will learn everything you need to know.
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English subtitle
Quality: 720p
4.42 GB
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