Oreilly - Optimization Algorithms, Video Edition

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Oreilly - Optimization Algorithms, Video Edition (Size: 3 GB)
  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 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 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 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 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 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 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 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 MB
  075. Chapter 11. Solving function optimization using supervised machine learning.mp4 18 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 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 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 409.6 B
  Get Bonus Downloads Here.url 204.8 B
  ▲ 110 total files

Description


Optimization Algorithms, Video Edition

https://DevCourseWeb.com

Released: 10/2024
Duration: 15h 54m | .MP4 1920x1080, 30 fps(r) | AAC, 48000 Hz, 2ch | 3 GB
Genre: eLearning | Language: English

In Video Editions the narrator reads the book while the content, figures, code listings, diagrams, and text appear on the screen. Like an audiobook that you can also watch as a video.

Solve design, planning, and control problems using modern AI techniques.

Optimization problems are everywhere in daily life. What’s the fastest route from one place to another? How do you calculate the optimal price for a product? How should you plant crops, allocate resources, and schedule surgeries? Optimization Algorithms introduces the AI algorithms that can solve these complex and poorly-structured problems.