Optimization Algorithms Video Edition DevCourseWeb
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| Torrent Hash : | 8D9D4F7AAEB56CFF5ED7F44B1DD53EC5DFCBA2B4 |
| Torrent Added : | at Dec. 2, 2024, 3:43 p.m. in Other |
| Torrent Size : | 3.0 GB |
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Optimization Algorithms Video Edition DevCourseWeb
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Optimization Algorithms Video Edition DevCourseWeb
Get Bonus Downloads Here.url -
001. Part 1. Deterministic search algorithms.mp4 -
002. Chapter 1. Introduction to search and optimization.mp4 -
003. Chapter 1. Going from toy problems to the real world.mp4 -
004. Chapter 1. Basic ingredients of optimization problems.mp4 -
005. Chapter 1. Well-structured problems vs. ill-structured problems.mp4 -
006. Chapter 1. Search algorithms and the search dilemma.mp4 -
007. Chapter 1. Summary.mp4 -
008. Chapter 2. A deeper look at search and optimization.mp4 -
009. Chapter 2. Classifying search and optimization algorithms.mp4 -
010. Chapter 2. Heuristics and metaheuristics.mp4 -
011. Chapter 2. Nature-inspired algorithms.mp4 -
012. Chapter 2. Summary.mp4 -
013. Chapter 3. Blind search algorithms.mp4 -
014. Chapter 3. Graph search.mp4 -
015. Chapter 3. Graph traversal algorithms.mp4 -
016. Chapter 3. Shortest path algorithms.mp4 -
017. Chapter 3. Applying blind search to the routing problem.mp4 -
018. Chapter 3. Summary.mp4 -
019. Chapter 4. Informed search algorithms.mp4 -
020. Chapter 4. Minimum spanning tree algorithms.mp4 -
021. Chapter 4. Shortest path algorithms.mp4 -
022. Chapter 4. Applying informed search to a routing problem.mp4 -
023. Chapter 4. Summary.mp4 -
024. Part 2. Trajectory-based algorithms.mp4 -
025. Chapter 5. Simulated annealing.mp4 -
026. Chapter 5. The simulated annealing algorithm.mp4 -
027. Chapter 5. Function optimization.mp4 -
028. Chapter 5. Solving Sudoku.mp4 -
029. Chapter 5. Solving TSP.mp4 -
030. Chapter 5. Solving a delivery semi-truck routing problem.mp4 -
031. Chapter 5. Summary.mp4 -
032. Chapter 6. Tabu search.mp4 -
033. Chapter 6. Tabu search algorithm.mp4 -
034. Chapter 6. Solving constraint satisfaction problems.mp4 -
035. Chapter 6. Solving continuous problems.mp4 -
036. Chapter 6. Solving TSP and routing problems.mp4 -
037. Chapter 6. Assembly line balancing problem.mp4 -
038. Chapter 6. Summary.mp4 -
039. Part 3. Evolutionary computing algorithms.mp4 -
040. Chapter 7. Genetic algorithms.mp4 -
041. Chapter 7. Introducing evolutionary computation.mp4 -
042. Chapter 7. Genetic algorithm building blocks.mp4 -
043. Chapter 7. Implementing genetic algorithms in Python.mp4 -
044. Chapter 7. Summary.mp4 -
045. Chapter 8. Genetic algorithm variants.mp4 -
046. Chapter 8. Real-valued GA.mp4 -
047. Chapter 8. Permutation-based GA.mp4 -
048. Chapter 8. Multi-objective optimization.mp4 -
049. Chapter 8. Adaptive GA.mp4 -
050. Chapter 8. Solving the traveling salesman problem.mp4 -
051. Chapter 8. PID tuning problem.mp4 -
052. Chapter 8. Political districting problem.mp4 -
053. Chapter 8. Summary.mp4 -
054. Part 4. Swarm intelligence algorithms.mp4 -
055. Chapter 9. Particle swarm optimization.mp4 -
056. Chapter 9. Continuous PSO.mp4 -
057. Chapter 9. Binary PSO.mp4 -
058. Chapter 9. Permutation-based PSO.mp4 -
059. Chapter 9. Adaptive PSO.mp4 -
060. Chapter 9. Solving the traveling salesman problem.mp4 -
061. Chapter 9. Neural network training using PSO.mp4 -
062. Chapter 9. Summary.mp4 -
063. Chapter 10. Other swarm intelligence algorithms to explore.mp4 -
064. Chapter 10. ACO metaheuristics.mp4 -
065. Chapter 10. ACO variants.mp4 -
066. Chapter 10. From hive to optimization.mp4 -
067. Chapter 10. Exploring the artificial bee colony algorithm.mp4 -
068. Chapter 10. Summary.mp4 -
069. Part 5. Machine learning-based methods.mp4 -
070. Chapter 11. Supervised and unsupervised learning.mp4 -
071. Chapter 11. Demystifying machine learning.mp4 -
072. Chapter 11. Machine learning with graphs.mp4 -
073. Chapter 11. Self-organizing maps.mp4 -
074. Chapter 11. Machine learning for optimization problems.mp4 -
075. Chapter 11. Solving function optimization using supervised machine learning.mp4 -
076. Chapter 11. Solving TSP using supervised graph machine learning.mp4 -
077. Chapter 11. Solving TSP using unsupervised machine learning.mp4 -
078. Chapter 11. Finding a convex hull.mp4 -
079. Chapter 11. Summary.mp4 -
080. Chapter 12. Reinforcement learning.mp4 -
081. Chapter 12. Optimization with reinforcement learning.mp4 -
082. Chapter 12. Balancing CartPole using A2C and PPO.mp4 -
083. Chapter 12. Autonomous coordination in mobile networks using PPO.mp4 -
084. Chapter 12. Solving the truck selection problem using contextual bandits.mp4 -
085. Chapter 12. Journey s end A final reflection.mp4 -
086. Chapter 12. Summary.mp4 -
087. Appendix A. Search and optimization libraries in Python.mp4 -
088. Appendix A. Mathematical programming solvers.mp4 -
089. Appendix A. Graph and mapping libraries.mp4 -
090. Appendix A. Metaheuristics optimization libraries.mp4 -
091. Appendix A. Machine learning libraries.mp4 -
092. Appendix A. Projects.mp4 -
093. Appendix B. Benchmarks and datasets.mp4 -
094. Appendix B. Combinatorial optimization benchmark datasets.mp4 -
095. Appendix B. Geospatial datasets.mp4 -
096. Appendix B. Machine learning datasets.mp4 -
097. Appendix B. Data folder.mp4 -
098. Appendix C. Exercises and solutions.mp4 -
099. Appendix C. Chapter 3 Blind search algorithms.mp4 -
100. Appendix C. Chapter 4 Informed search algorithms.mp4 -
101. Appendix C. Chapter 5 Simulated annealing.mp4 -
102. Appendix C. Chapter 6 Tabu search.mp4 -
103. Appendix C. Chapter 7 Genetic algorithm.mp4 -
104. Appendix C. Chapter 8 Genetic algorithm variants.mp4 -
105. Appendix C. Chapter 9 Particle swarm optimization.mp4 -
106. Appendix C. Chapter 10 Other swarm intelligence algorithms to explore.mp4 -
107. Appendix C. Chapter 11 Supervised and unsupervised learning.mp4 -
108. Appendix C. Chapter 12 Reinforcement learning.mp4 -
Bonus Resources.txt -
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Get Bonus Downloads Here.url -
182 bytes
001. Part 1. Deterministic search algorithms.mp4 -
6.3 MB
002. Chapter 1. Introduction to search and optimization.mp4 -
24.2 MB
003. Chapter 1. Going from toy problems to the real world.mp4 -
7.9 MB
004. Chapter 1. Basic ingredients of optimization problems.mp4 -
26.8 MB
005. Chapter 1. Well-structured problems vs. ill-structured problems.mp4 -
22.4 MB
006. Chapter 1. Search algorithms and the search dilemma.mp4 -
7.5 MB
007. Chapter 1. Summary.mp4 -
5.5 MB
008. Chapter 2. A deeper look at search and optimization.mp4 -
168.4 MB
009. Chapter 2. Classifying search and optimization algorithms.mp4 -
21.8 MB
010. Chapter 2. Heuristics and metaheuristics.mp4 -
35.1 MB
011. Chapter 2. Nature-inspired algorithms.mp4 -
18.4 MB
012. Chapter 2. Summary.mp4 -
5.5 MB
013. Chapter 3. Blind search algorithms.mp4 -
44.7 MB
014. Chapter 3. Graph search.mp4 -
11.6 MB
015. Chapter 3. Graph traversal algorithms.mp4 -
49.4 MB
016. Chapter 3. Shortest path algorithms.mp4 -
28.5 MB
017. Chapter 3. Applying blind search to the routing problem.mp4 -
23.4 MB
018. Chapter 3. Summary.mp4 -
6.5 MB
019. Chapter 4. Informed search algorithms.mp4 -
12.3 MB
020. Chapter 4. Minimum spanning tree algorithms.mp4 -
23.9 MB
021. Chapter 4. Shortest path algorithms.mp4 -
126.4 MB
022. Chapter 4. Applying informed search to a routing problem.mp4 -
42.3 MB
023. Chapter 4. Summary.mp4 -
6.7 MB
024. Part 2. Trajectory-based algorithms.mp4 -
4.9 MB
025. Chapter 5. Simulated annealing.mp4 -
10.7 MB
026. Chapter 5. The simulated annealing algorithm.mp4 -
75.3 MB
027. Chapter 5. Function optimization.mp4 -
35.7 MB
028. Chapter 5. Solving Sudoku.mp4 -
22.5 MB
029. Chapter 5. Solving TSP.mp4 -
26.8 MB
030. Chapter 5. Solving a delivery semi-truck routing problem.mp4 -
20.3 MB
031. Chapter 5. Summary.mp4 -
7.2 MB
032. Chapter 6. Tabu search.mp4 -
17.0 MB
033. Chapter 6. Tabu search algorithm.mp4 -
49.7 MB
034. Chapter 6. Solving constraint satisfaction problems.mp4 -
15.1 MB
035. Chapter 6. Solving continuous problems.mp4 -
9.7 MB
036. Chapter 6. Solving TSP and routing problems.mp4 -
36.1 MB
037. Chapter 6. Assembly line balancing problem.mp4 -
45.9 MB
038. Chapter 6. Summary.mp4 -
4.0 MB
039. Part 3. Evolutionary computing algorithms.mp4 -
4.9 MB
040. Chapter 7. Genetic algorithms.mp4 -
38.7 MB
041. Chapter 7. Introducing evolutionary computation.mp4 -
28.5 MB
042. Chapter 7. Genetic algorithm building blocks.mp4 -
51.4 MB
043. Chapter 7. Implementing genetic algorithms in Python.mp4 -
40.2 MB
044. Chapter 7. Summary.mp4 -
9.6 MB
045. Chapter 8. Genetic algorithm variants.mp4 -
18.5 MB
046. Chapter 8. Real-valued GA.mp4 -
48.0 MB
047. Chapter 8. Permutation-based GA.mp4 -
27.5 MB
048. Chapter 8. Multi-objective optimization.mp4 -
20.3 MB
049. Chapter 8. Adaptive GA.mp4 -
11.0 MB
050. Chapter 8. Solving the traveling salesman problem.mp4 -
8.4 MB
051. Chapter 8. PID tuning problem.mp4 -
24.3 MB
052. Chapter 8. Political districting problem.mp4 -
27.3 MB
053. Chapter 8. Summary.mp4 -
7.8 MB
054. Part 4. Swarm intelligence algorithms.mp4 -
5.4 MB
055. Chapter 9. Particle swarm optimization.mp4 -
40.0 MB
056. Chapter 9. Continuous PSO.mp4 -
81.3 MB
057. Chapter 9. Binary PSO.mp4 -
11.8 MB
058. Chapter 9. Permutation-based PSO.mp4 -
7.3 MB
059. Chapter 9. Adaptive PSO.mp4 -
14.9 MB
060. Chapter 9. Solving the traveling salesman problem.mp4 -
14.9 MB
061. Chapter 9. Neural network training using PSO.mp4 -
71.1 MB
062. Chapter 9. Summary.mp4 -
3.8 MB
063. Chapter 10. Other swarm intelligence algorithms to explore.mp4 -
29.9 MB
064. Chapter 10. ACO metaheuristics.mp4 -
21.4 MB
065. Chapter 10. ACO variants.mp4 -
67.7 MB
066. Chapter 10. From hive to optimization.mp4 -
31.0 MB
067. Chapter 10. Exploring the artificial bee colony algorithm.mp4 -
38.7 MB
068. Chapter 10. Summary.mp4 -
8.4 MB
069. Part 5. Machine learning-based methods.mp4 -
5.4 MB
070. Chapter 11. Supervised and unsupervised learning.mp4 -
18.0 MB
071. Chapter 11. Demystifying machine learning.mp4 -
26.7 MB
072. Chapter 11. Machine learning with graphs.mp4 -
122.7 MB
073. Chapter 11. Self-organizing maps.mp4 -
12.3 MB
074. Chapter 11. Machine learning for optimization problems.mp4 -
19.0 MB
075. Chapter 11. Solving function optimization using supervised machine learning.mp4 -
18.0 MB
076. Chapter 11. Solving TSP using supervised graph machine learning.mp4 -
39.2 MB
077. Chapter 11. Solving TSP using unsupervised machine learning.mp4 -
8.1 MB
078. Chapter 11. Finding a convex hull.mp4 -
36.5 MB
079. Chapter 11. Summary.mp4 -
6.9 MB
080. Chapter 12. Reinforcement learning.mp4 -
135.9 MB
081. Chapter 12. Optimization with reinforcement learning.mp4 -
23.3 MB
082. Chapter 12. Balancing CartPole using A2C and PPO.mp4 -
50.3 MB
083. Chapter 12. Autonomous coordination in mobile networks using PPO.mp4 -
19.9 MB
084. Chapter 12. Solving the truck selection problem using contextual bandits.mp4 -
32.0 MB
085. Chapter 12. Journey s end A final reflection.mp4 -
6.1 MB
086. Chapter 12. Summary.mp4 -
10.2 MB
087. Appendix A. Search and optimization libraries in Python.mp4 -
16.7 MB
088. Appendix A. Mathematical programming solvers.mp4 -
27.7 MB
089. Appendix A. Graph and mapping libraries.mp4 -
49.2 MB
090. Appendix A. Metaheuristics optimization libraries.mp4 -
34.8 MB
091. Appendix A. Machine learning libraries.mp4 -
34.0 MB
092. Appendix A. Projects.mp4 -
5.7 MB
093. Appendix B. Benchmarks and datasets.mp4 -
7.9 MB
094. Appendix B. Combinatorial optimization benchmark datasets.mp4 -
10.5 MB
095. Appendix B. Geospatial datasets.mp4 -
3.8 MB
096. Appendix B. Machine learning datasets.mp4 -
4.9 MB
097. Appendix B. Data folder.mp4 -
6.2 MB
098. Appendix C. Exercises and solutions.mp4 -
34.4 MB
099. Appendix C. Chapter 3 Blind search algorithms.mp4 -
17.9 MB
100. Appendix C. Chapter 4 Informed search algorithms.mp4 -
19.7 MB
101. Appendix C. Chapter 5 Simulated annealing.mp4 -
25.9 MB
102. Appendix C. Chapter 6 Tabu search.mp4 -
26.5 MB
103. Appendix C. Chapter 7 Genetic algorithm.mp4 -
27.2 MB
104. Appendix C. Chapter 8 Genetic algorithm variants.mp4 -
34.4 MB
105. Appendix C. Chapter 9 Particle swarm optimization.mp4 -
59.3 MB
106. Appendix C. Chapter 10 Other swarm intelligence algorithms to explore.mp4 -
32.8 MB
107. Appendix C. Chapter 11 Supervised and unsupervised learning.mp4 -
20.4 MB
108. Appendix C. Chapter 12 Reinforcement learning.mp4 -
61.9 MB
Bonus Resources.txt -
386 bytes
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