Oreilly - Optimization Algorithms, Video Edition

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[ DevCourseWeb.com ] Oreilly - Optimization Algorithms, Video Edition
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    • 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

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.



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Oreilly - Optimization Algorithms, Video Edition

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