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1. Cycle GAN.mp4
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32.7 MB
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1. Cycle GAN.srt
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2.5 KB
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1. Image-To-Image Translation.mp4
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62.1 MB
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1. Image-To-Image Translation.srt
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4.1 KB
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1. Introduction.mp4
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MP4
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65 MB
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1. Introduction.srt
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5.4 KB
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1. MNIST using GAN.mp4
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14.2 MB
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1. MNIST using GAN.srt
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1. Machine Learning.mp4
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84.5 MB
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1. Machine Learning.srt
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1. Neural Networks.mp4
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85.6 MB
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1. Neural Networks.srt
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1. What is Deep Learning.mp4
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40.4 MB
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1. What is Deep Learning.srt
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2.7 KB
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1. What is a GAN.mp4
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MP4
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28.7 MB
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1. What is a GAN.srt
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2.6 KB
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1.1 Deep Learning.html
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204.8 B
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1.1 Generative Adversarial Nets.html
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102.4 B
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1.1 Introduction.pdf
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PDF
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2.5 MB
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1.1 Lecture 2.pdf
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PDF
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1 MB
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1.1 Neural Networks and Learning Machines.html
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102.4 B
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1.2 Probabilistic Machine Learning Advanced Topics.html
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102.4 B
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10. Convolutional Neural Networks (CNNs).html
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204.8 B
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10. DCGANs.html
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204.8 B
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10. Define and Train the Model.mp4
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MP4
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14.9 MB
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10. Define and Train the Model.srt
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1.5 KB
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10. Pix2Pix.html
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204.8 B
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10. Semi-Supervised Learning.html
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204.8 B
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10. Single-Layer Neural Networks (Perceptron).html
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204.8 B
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11. Convolutional Neural Networks (CNNs).html
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204.8 B
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11. Define and Train the Model.html
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204.8 B
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11. Learning Methods Comparison.mp4
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29.9 MB
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11. Learning Methods Comparison.srt
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2.2 KB
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11. Multi-Layer Neural Networks.mp4
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39.3 MB
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11. Multi-Layer Neural Networks.srt
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2.9 KB
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11. SGAN.mp4
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MP4
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14.7 MB
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11. SGAN.srt
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1.5 KB
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11.1 Multilayer Perceptron.html
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102.4 B
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11.1 SuperVize Me What’s the Difference Between Supervised, Unsupervised, Semi-Supervised and Reinforcement Learning.html
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102.4 B
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12. Learning Methods Comparison.html
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204.8 B
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12. Multi-Layer Neural Networks.html
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204.8 B
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12. Recurrent Neural Networks(RNNs).mp4
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57.5 MB
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12. Recurrent Neural Networks(RNNs).srt
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5.8 KB
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12. SGAN.html
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204.8 B
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12. Train the Model.html
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204.8 B
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12.1 Recurrent Neural Networks.html
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102.4 B
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13. Activation Functions.mp4
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22.5 MB
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13. Activation Functions.srt
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2.1 KB
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13. Conditional GAN.mp4
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19.2 MB
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13. Conditional GAN.srt
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2.2 KB
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13. DCGAN-MNIST.html
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204.8 B
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13. Recurrent Neural Networks(RNNs).html
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204.8 B
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13. Reinforcement Learning.mp4
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39.7 MB
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13. Reinforcement Learning.srt
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3.4 KB
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13.1 Reinforcement Learning A Survey.html
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102.4 B
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13.1 What is an Activation Function.html
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102.4 B
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14. Activation Functions.html
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204.8 B
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14. Conditional GAN.html
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204.8 B
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14. DCGAN-Fashion.html
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204.8 B
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14. Recurrent Neural Networks(RNNs).html
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204.8 B
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14. Reinforcement Learning.html
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204.8 B
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15. Cycle GAN.mp4
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MP4
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26.2 MB
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15. Cycle GAN.srt
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2.1 KB
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15. Learning Example.mp4
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31.9 MB
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15. Learning Example.srt
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2.6 KB
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15. Neural Network Example with Number.mp4
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23.5 MB
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15. Neural Network Example with Number.srt
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1.7 KB
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15. Recurrent Neural Networks(RNNs).html
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204.8 B
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15.1 Machine Learning 6 Real-World Examples.html
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102.4 B
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16. Cycle GAN.html
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HTML
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204.8 B
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16. Learning Example.html
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204.8 B
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16. Long Short-Term Memory (LSTM).mp4
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MP4
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28.5 MB
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16. Long Short-Term Memory (LSTM).srt
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SRT
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4.1 KB
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16. Neural Networks Example with Number.html
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204.8 B
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16.1 Understanding LSTM Networks.html
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HTML
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204.8 B
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17. Classification.html
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HTML
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204.8 B
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17. Cycle GAN.html
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204.8 B
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17. Design a Learning System.mp4
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MP4
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50 MB
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17. Design a Learning System.srt
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4.3 KB
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17. Long Short-Term Memory (LSTM).html
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204.8 B
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17.1 Machine Learning.html
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102.4 B
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18. Design a Learning System.html
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204.8 B
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18. Long Short-Term Memory (LSTM).html
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204.8 B
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18. Simple GAN.html
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204.8 B
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19. Deep Dream.html
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204.8 B
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19. Design a Learning System.html
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204.8 B
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19. Long Short-Term Memory (LSTM).html
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204.8 B
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2. Cycle GAN.html
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HTML
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204.8 B
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2. Image-To-Image Translation.html
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HTML
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204.8 B
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2. MNIST using GAN.html
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HTML
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204.8 B
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2. Machine Learning.html
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204.8 B
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2. Neural Networks.html
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204.8 B
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2. What is Deep Learning.html
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204.8 B
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2. What is a GAN.html
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204.8 B
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20. Leaning Error Types.mp4
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20.1 MB
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20. Leaning Error Types.srt
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1.6 KB
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20. Residual Neural Network Learning (ResNets).mp4
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24.5 MB
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20. Residual Neural Network Learning (ResNets).srt
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2.5 KB
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20. Style Transfer.html
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204.8 B
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20.1 Probabilistic Machine Learning Advanced Topics.html
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102.4 B
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21. Leaning Error Types.html
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204.8 B
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21. Residual Neural Network Learning (ResNets).html
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204.8 B
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22. Classification flowers.html
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204.8 B
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22. Underfitting and Overfitting.mp4
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MP4
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13.6 MB
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22. Underfitting and Overfitting.srt
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1.3 KB
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22.1 Underfitting and Overfitting in Machine Learning.html
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204.8 B
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23. CNN.html
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204.8 B
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23. Underfitting and Overfitting.html
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204.8 B
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24. Text Classification RNN.html
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204.8 B
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24. Underfitting and Overfitting.html
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204.8 B
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25. Linear Regression.html
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204.8 B
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26. SVM.html
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204.8 B
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27. Classification model Benchmark.html
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204.8 B
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3. Build and Test the Generator.mp4
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MP4
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36.4 MB
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3. Build and Test the Generator.srt
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SRT
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2.5 KB
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3. Cycle GAN.html
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HTML
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204.8 B
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3. Initial Setup.mp4
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MP4
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91.7 MB
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3. Initial Setup.srt
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7.6 KB
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3. Machine Learning.html
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204.8 B
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3. Neural Networks.html
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204.8 B
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3. What is Deep Learning.html
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204.8 B
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3. What is a GAN.html
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204.8 B
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4. Build and Test the Generator.html
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204.8 B
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4. Cycle GAN.html
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204.8 B
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4. Deep Learning Applications.mp4
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42.9 MB
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4. Deep Learning Applications.srt
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2.6 KB
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4. GAN Applications.mp4
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MP4
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11.7 MB
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4. GAN Applications.srt
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921.6 B
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4. Initial Setup.html
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204.8 B
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4. Machine Learning.html
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204.8 B
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4. Neural Networks.html
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204.8 B
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4.1 Applications of GANs.html
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102.4 B
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4.1 Deep Learning Methods and Applications.html
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102.4 B
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5. Build the Discriminator.mp4
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MP4
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7.3 MB
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5. Build the Discriminator.srt
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1.8 KB
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5. Deep Learning Applications.html
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204.8 B
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5. GAN Applications.html
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204.8 B
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5. MMNIST Handwritten Digit Dataset.mp4
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MP4
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12.3 MB
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5. MMNIST Handwritten Digit Dataset.srt
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1.2 KB
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5. Neural Networks.html
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204.8 B
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5. Supervised Learning.mp4
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MP4
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41 MB
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5. Supervised Learning.srt
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4.1 KB
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5.1 Artificial Intelligence A Modern Approach.html
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102.4 B
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5.1 MNIST.html
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HTML
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102.4 B
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6. Build the Discriminator.html
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HTML
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204.8 B
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6. Deep Learning Algorithms and Architectures.mp4
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MP4
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12.1 MB
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6. Deep Learning Algorithms and Architectures.srt
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1.1 KB
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6. MMNIST Handwritten Digit Dataset.html
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204.8 B
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6. Neural Networks.html
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204.8 B
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6. Supervised Learning.html
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204.8 B
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6. Type of GANs.mp4
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MP4
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14.8 MB
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6. Type of GANs.srt
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819.2 B
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6.1 Deep Learning.html
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HTML
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204.8 B
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6.1 GAN Applications.html
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102.4 B
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7. Deep Learning Algorithms and Architectures.html
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HTML
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204.8 B
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7. Load and Prepare the Dataset.mp4
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MP4
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64.1 MB
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7. Load and Prepare the Dataset.srt
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6.2 KB
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7. Neural Networks.html
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204.8 B
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7. Training and Generate Image.mp4
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MP4
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52.2 MB
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7. Training and Generate Image.srt
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2.4 KB
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7. Type of GANs.html
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204.8 B
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7. Unsupervised Learning.mp4
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MP4
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34.3 MB
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7. Unsupervised Learning.srt
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3.6 KB
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7.1 Unsupervised Learning Foundations of Neural Computation.html
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102.4 B
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8. Applications of Artificial Neural Networks.mp4
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MP4
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9.2 MB
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8. Applications of Artificial Neural Networks.srt
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2.2 KB
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8. Convolutional Neural Networks (CNNs).mp4
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MP4
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48.9 MB
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8. Convolutional Neural Networks (CNNs).srt
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5.1 KB
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8. Create the Models.mp4
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MP4
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77.7 MB
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8. Create the Models.srt
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SRT
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6.8 KB
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8. DCGANs.mp4
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MP4
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30.2 MB
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8. DCGANs.srt
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SRT
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3.1 KB
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8. Training and Generate Image.html
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HTML
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204.8 B
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8. Unsupervised Learning.html
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HTML
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204.8 B
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8.1 Applications of neural networks.html
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HTML
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204.8 B
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8.1 What is a Convolutional Neural Network.html
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HTML
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512 B
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9. Conditional GAN.html
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HTML
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204.8 B
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9. Convolutional Neural Networks (CNNs).html
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HTML
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204.8 B
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9. Create the Models.html
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204.8 B
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9. DCGANs.html
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HTML
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204.8 B
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9. Semi-Supervised Learning.mp4
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MP4
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23 MB
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9. Semi-Supervised Learning.srt
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3 KB
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9. Single-Layer Neural Networks (Perceptron).mp4
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MP4
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19.2 MB
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9. Single-Layer Neural Networks (Perceptron).srt
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SRT
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1.6 KB
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9.1 Semi-Supervised Learning Literature Survey.html
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HTML
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102.4 B
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9.1 What is a Perceptron.html
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HTML
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102.4 B
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Bonus Resources.txt
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TXT
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307.2 B
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Get Bonus Downloads Here.url
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URL
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204.8 B
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