DevCourseWeb com Oreilly Optimization Algorithms Video Edition | 8D9D4F7AAEB56CFF5ED7F44B1DD53EC5DFCBA2B4

DevCourseWeb com Oreilly Optimization Algorithms Video Edition

Name	[ DevCourseWeb.com ] Oreilly - Optimization Algorithms, Video Edition	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	3.2 GB
Total Files	110
Last Seen	2025-04-15 23:59
Hash	8D9D4F7AAEB56CFF5ED7F44B1DD53EC5DFCBA2B4

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001. Part 1. Deterministic search algorithms.mp4	6.6 MB
002. Chapter 1. Introduction to search and optimization.mp4	25.4 MB
003. Chapter 1. Going from toy problems to the real world.mp4	8.3 MB
004. Chapter 1. Basic ingredients of optimization problems.mp4	28.1 MB
005. Chapter 1. Well-structured problems vs. ill-structured problems.mp4	23.5 MB
006. Chapter 1. Search algorithms and the search dilemma.mp4	7.9 MB
007. Chapter 1. Summary.mp4	5.8 MB
008. Chapter 2. A deeper look at search and optimization.mp4	176.6 MB
009. Chapter 2. Classifying search and optimization algorithms.mp4	22.9 MB
010. Chapter 2. Heuristics and metaheuristics.mp4	36.8 MB
011. Chapter 2. Nature-inspired algorithms.mp4	19.3 MB
012. Chapter 2. Summary.mp4	5.8 MB
013. Chapter 3. Blind search algorithms.mp4	46.8 MB
014. Chapter 3. Graph search.mp4	12.2 MB
015. Chapter 3. Graph traversal algorithms.mp4	51.8 MB
016. Chapter 3. Shortest path algorithms.mp4	29.9 MB
017. Chapter 3. Applying blind search to the routing problem.mp4	24.6 MB
018. Chapter 3. Summary.mp4	6.8 MB
019. Chapter 4. Informed search algorithms.mp4	12.9 MB
020. Chapter 4. Minimum spanning tree algorithms.mp4	25.1 MB
021. Chapter 4. Shortest path algorithms.mp4	132.5 MB
022. Chapter 4. Applying informed search to a routing problem.mp4	44.4 MB
023. Chapter 4. Summary.mp4	7.1 MB
024. Part 2. Trajectory-based algorithms.mp4	5.1 MB
025. Chapter 5. Simulated annealing.mp4	11.2 MB
026. Chapter 5. The simulated annealing algorithm.mp4	78.9 MB
027. Chapter 5. Function optimization.mp4	37.4 MB
028. Chapter 5. Solving Sudoku.mp4	23.6 MB
029. Chapter 5. Solving TSP.mp4	28.1 MB
030. Chapter 5. Solving a delivery semi-truck routing problem.mp4	21.3 MB
031. Chapter 5. Summary.mp4	7.6 MB
032. Chapter 6. Tabu search.mp4	17.9 MB
033. Chapter 6. Tabu search algorithm.mp4	52.1 MB
034. Chapter 6. Solving constraint satisfaction problems.mp4	15.8 MB
035. Chapter 6. Solving continuous problems.mp4	10.2 MB
036. Chapter 6. Solving TSP and routing problems.mp4	37.9 MB
037. Chapter 6. Assembly line balancing problem.mp4	48.1 MB
038. Chapter 6. Summary.mp4	4.2 MB
039. Part 3. Evolutionary computing algorithms.mp4	5.2 MB
040. Chapter 7. Genetic algorithms.mp4	40.6 MB
041. Chapter 7. Introducing evolutionary computation.mp4	29.9 MB
042. Chapter 7. Genetic algorithm building blocks.mp4	53.9 MB
043. Chapter 7. Implementing genetic algorithms in Python.mp4	42.2 MB
044. Chapter 7. Summary.mp4	10.1 MB
045. Chapter 8. Genetic algorithm variants.mp4	19.4 MB
046. Chapter 8. Real-valued GA.mp4	50.4 MB
047. Chapter 8. Permutation-based GA.mp4	28.8 MB
048. Chapter 8. Multi-objective optimization.mp4	21.2 MB
049. Chapter 8. Adaptive GA.mp4	11.5 MB
050. Chapter 8. Solving the traveling salesman problem.mp4	8.8 MB
051. Chapter 8. PID tuning problem.mp4	25.5 MB
052. Chapter 8. Political districting problem.mp4	28.6 MB
053. Chapter 8. Summary.mp4	8.1 MB
054. Part 4. Swarm intelligence algorithms.mp4	5.7 MB
055. Chapter 9. Particle swarm optimization.mp4	42.0 MB
056. Chapter 9. Continuous PSO.mp4	85.3 MB
057. Chapter 9. Binary PSO.mp4	12.4 MB
058. Chapter 9. Permutation-based PSO.mp4	7.7 MB
059. Chapter 9. Adaptive PSO.mp4	15.6 MB
060. Chapter 9. Solving the traveling salesman problem.mp4	15.6 MB
061. Chapter 9. Neural network training using PSO.mp4	74.5 MB
062. Chapter 9. Summary.mp4	4.0 MB
063. Chapter 10. Other swarm intelligence algorithms to explore.mp4	31.3 MB
064. Chapter 10. ACO metaheuristics.mp4	22.4 MB
065. Chapter 10. ACO variants.mp4	71.0 MB
066. Chapter 10. From hive to optimization.mp4	32.5 MB
067. Chapter 10. Exploring the artificial bee colony algorithm.mp4	40.6 MB
068. Chapter 10. Summary.mp4	8.8 MB
069. Part 5. Machine learning-based methods.mp4	5.7 MB
070. Chapter 11. Supervised and unsupervised learning.mp4	18.9 MB
071. Chapter 11. Demystifying machine learning.mp4	28.0 MB
072. Chapter 11. Machine learning with graphs.mp4	128.7 MB
073. Chapter 11. Self-organizing maps.mp4	12.9 MB
074. Chapter 11. Machine learning for optimization problems.mp4	19.9 MB
075. Chapter 11. Solving function optimization using supervised machine learning.mp4	18.9 MB
076. Chapter 11. Solving TSP using supervised graph machine learning.mp4	41.1 MB
077. Chapter 11. Solving TSP using unsupervised machine learning.mp4	8.5 MB
078. Chapter 11. Finding a convex hull.mp4	38.3 MB
079. Chapter 11. Summary.mp4	7.3 MB
080. Chapter 12. Reinforcement learning.mp4	142.5 MB
081. Chapter 12. Optimization with reinforcement learning.mp4	24.5 MB
082. Chapter 12. Balancing CartPole using A2C and PPO.mp4	52.8 MB
083. Chapter 12. Autonomous coordination in mobile networks using PPO.mp4	20.8 MB
084. Chapter 12. Solving the truck selection problem using contextual bandits.mp4	33.6 MB
085. Chapter 12. Journey s end A final reflection.mp4	6.4 MB
086. Chapter 12. Summary.mp4	10.7 MB
087. Appendix A. Search and optimization libraries in Python.mp4	17.5 MB
088. Appendix A. Mathematical programming solvers.mp4	29.0 MB
089. Appendix A. Graph and mapping libraries.mp4	51.6 MB
090. Appendix A. Metaheuristics optimization libraries.mp4	36.4 MB
091. Appendix A. Machine learning libraries.mp4	35.7 MB
092. Appendix A. Projects.mp4	6.0 MB
093. Appendix B. Benchmarks and datasets.mp4	8.3 MB
094. Appendix B. Combinatorial optimization benchmark datasets.mp4	11.0 MB
095. Appendix B. Geospatial datasets.mp4	4.0 MB
096. Appendix B. Machine learning datasets.mp4	5.1 MB
097. Appendix B. Data folder.mp4	6.5 MB
098. Appendix C. Exercises and solutions.mp4	36.1 MB
099. Appendix C. Chapter 3 Blind search algorithms.mp4	18.8 MB
100. Appendix C. Chapter 4 Informed search algorithms.mp4	20.6 MB
101. Appendix C. Chapter 5 Simulated annealing.mp4	27.1 MB
102. Appendix C. Chapter 6 Tabu search.mp4	27.8 MB
103. Appendix C. Chapter 7 Genetic algorithm.mp4	28.5 MB
104. Appendix C. Chapter 8 Genetic algorithm variants.mp4	36.1 MB
105. Appendix C. Chapter 9 Particle swarm optimization.mp4	62.2 MB
106. Appendix C. Chapter 10 Other swarm intelligence algorithms to explore.mp4	34.4 MB
107. Appendix C. Chapter 11 Supervised and unsupervised learning.mp4	21.4 MB
108. Appendix C. Chapter 12 Reinforcement learning.mp4	64.9 MB
Bonus Resources.txt	0.4 KB
Total files 110