Oreilly - Evolutionary Deep Learning, Video Edition

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• 001. Part 1. Getting started.mp4 (3.4 MB)
• 002. Chapter 1. Introducing evolutionary deep learning.mp4 (30.5 MB)
• 003. Chapter 1. The why and where of evolutionary deep learning.mp4 (3.6 MB)
• 004. Chapter 1. The need for deep learning optimization.mp4 (13.3 MB)
• 005. Chapter 1. Automating optimization with automated machine learning.mp4 (19.9 MB)
• 006. Chapter 1. Applications of evolutionary deep learning.mp4 (16.0 MB)
• 007. Chapter 1. Summary.mp4 (3.2 MB)
• 008. Chapter 2. Introducing evolutionary computation.mp4 (13.5 MB)
• 009. Chapter 2. Simulating life with Python.mp4 (10.2 MB)
• 010. Chapter 2. Life simulation as optimization.mp4 (11.9 MB)
• 011. Chapter 2. Adding evolution to the life simulation.mp4 (26.0 MB)
• 012. Chapter 2. Genetic algorithms in Python.mp4 (48.4 MB)
• 013. Chapter 2. Summary.mp4 (7.4 MB)
• 014. Chapter 3. Introducing genetic algorithms with DEAP.mp4 (20.1 MB)
• 015. Chapter 3. Solving the Queen’s Gambit.mp4 (15.1 MB)
• 016. Chapter 3. Helping a traveling salesman.mp4 (23.5 MB)
• 017. Chapter 3. Selecting genetic operators for improved evolution.mp4 (27.5 MB)
• 018. Chapter 3. Painting with the EvoLisa.mp4 (19.5 MB)
• 019. Chapter 3. Summary.mp4 (5.5 MB)
• 020. Chapter 4. More evolutionary computation with DEAP.mp4 (35.6 MB)
• 021. Chapter 4. Particle swarm optimization with DEAP.mp4 (18.0 MB)
• 022. Chapter 4. Coevolving solutions with DEAP.mp4 (22.5 MB)
• 023. Chapter 4. Evolutionary strategies with DEAP.mp4 (30.3 MB)
• 024. Chapter 4. Differential evolution with DEAP.mp4 (19.4 MB)
• 025. Chapter 4. Summary.mp4 (3.9 MB)
• 026. Part 2. Optimizing deep learning.mp4 (2.4 MB)
• 027. Chapter 5. Automating hyperparameter optimization.mp4 (36.7 MB)
• 028. Chapter 5. Automating HPO with random search.mp4 (22.2 MB)
• 029. Chapter 5. Grid search and HPO.mp4 (21.9 MB)
• 030. Chapter 5. Evolutionary computation for HPO.mp4 (21.4 MB)
• 031. Chapter 5. Genetic algorithms and evolutionary strategies for HPO.mp4 (20.4 MB)
• 032. Chapter 5. Differential evolution for HPO.mp4 (14.0 MB)
• 033. Chapter 5. Summary.mp4 (4.1 MB)
• 034. Chapter 6. Neuroevolution optimization.mp4 (16.7 MB)
• 035. Chapter 6. Genetic algorithms as deep learning optimizers.mp4 (13.7 MB)
• 036. Chapter 6. Other evolutionary methods for neurooptimization.mp4 (7.4 MB)
• 037. Chapter 6. Applying neuroevolution optimization to Keras.mp4 (13.3 MB)
• 038. Chapter 6. Understanding the limits of evolutionary optimization.mp4 (9.5 MB)
• 039. Chapter 6. Summary.mp4 (4.1 MB)
• 040. Chapter 7. Evolutionary convolutional neural networks.mp4 (28.7 MB)
• 041. Chapter 7. Encoding a network architecture in genes.mp4 (14.2 MB)
• 042. Chapter 7. Creating the mating crossover operation.mp4 (10.2 MB)
• 043. Chapter 7. Developing a custom mutation operator.mp4 (13.0 MB)
• 044. Chapter 7. Evolving convolutional network architecture.mp4 (17.5 MB)
• 045. Chapter 7. Summary.mp4 (3.7 MB)
• 046. Part 3. Advanced applications.mp4 (4.9 MB)
• 047. Chapter 8. Evolving autoencoders.mp4 (30.5 MB)
• 048. Chapter 8. Evolutionary AE optimization.mp4 (17.6 MB)
• 049. Chapter 8. Mating and mutating the autoencoder gene sequence.mp4 (9.8 MB)
• 050. Chapter 8. Evolving an autoencoder.mp4 (9.7 MB)
• 051. Chapter 8. Building variational autoencoders.mp4 (29.8 MB)
• 052. Chapter 8. Summary.mp4 (5.1 MB)
• 053. Chapter 9. Generative deep learning and evolution.mp4 (29.3 MB)
• 054. Chapter 9. The challenges of training a GAN.mp4 (29.4 MB)
• 055. Chapter 9. Fixing GAN problems with Wasserstein loss.mp4 (13.8 MB)
• 056. Chapter 9. Encoding the Wasserstein DCGAN for evolution.mp4 (14.7 MB)
• 057. Chapter 9. Optimizing the DCGAN with genetic algorithms.mp4 (11.2 MB)
• 058. Chapter 9. Summary.mp4 (3.7 MB)
• 059. Chapter 10. NEAT NeuroEvolution of Augmenting Topologies.mp4 (24.4 MB)
• 060. Chapter 10. Visualizing an evolved NEAT network.mp4 (10.7 MB)
• 061. Chapter 10. Exercising the capabilities of NEAT.mp4 (15.3 MB)
• 062. Chapter 10. Exercising NEAT to classify images.mp4 (17.4 MB)
• 063. Chapter 10. Uncovering the role of speciation in evolving topologies.mp4 (24.1 MB)
• 064. Chapter 10. Summary.mp4 (3.3 MB)
• 065. Chapter 11. Evolutionary learning with NEAT.mp4 (32.4 MB)
• 066. Chapter 11. Exploring complex problems from the OpenAI Gym.mp4 (15.3 MB)
• 067. Chapter 11. Solving reinforcement learning problems with NEAT.mp4 (14.7 MB)
• 068. Chapter 11. Solving Gym’s lunar lander problem with NEAT agents.mp4 (16.5 MB)
• 069. Chapter 11. Solving Gym’s lunar lander problem with a deep Q-network.mp4 (16.3 MB)
• 070. Chapter 11. Summary.mp4 (3.6 MB)
• 071. Chapter 12. Evolutionary machine learning and beyond.mp4 (25.1 MB)
• 072. Chapter 12. Revisiting reinforcement learning with Geppy.mp4 (15.5 MB)
• 073. Chapter 12. Introducing instinctual learning.mp4 (34.6 MB)
• 074. Chapter 12. Generalized learning with genetic programming.mp4 (24.6 MB)
• 075. Chapter 12. The future of evolutionary machine learning.mp4 (22.4 MB)
• 076. Chapter 12. Generalization with instinctual deep and deep reinforcement learning.mp4 (19.8 MB)
• 077. Chapter 12. Summary.mp4 (4.0 MB)
• Bonus Resources.txt (0.4 KB)