[Tutorialsplanet.NET] Udemy - The Complete Neural Networks Bootcamp Theory, Applications torrent, magnet, bt

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[Tutorialsplanet.NET] Udemy - The Complete Neural Networks Bootcamp Theory, Applications

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Tutorialsplanet NET Udemy The Complete Neural Networks Bootcamp Theory Applications

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File Name

Size

1. How Neural Networks and Backpropagation Works/1. What Can Deep Learning Do-en_US.srt

18.21KB

1. How Neural Networks and Backpropagation Works/1. What Can Deep Learning Do.mp4

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1. How Neural Networks and Backpropagation Works/2. The Rise of Deep Learning-en_US.srt

8.13KB

1. How Neural Networks and Backpropagation Works/2. The Rise of Deep Learning.mp4

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1. How Neural Networks and Backpropagation Works/3. The Essence of Neural Networks-en_US.srt

12.75KB

1. How Neural Networks and Backpropagation Works/3. The Essence of Neural Networks.mp4

49.99MB

1. How Neural Networks and Backpropagation Works/4. The Perceptron-en_US.srt

21.2KB

1. How Neural Networks and Backpropagation Works/4. The Perceptron.mp4

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1. How Neural Networks and Backpropagation Works/5. Gradient Descent-en_US.srt

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1. How Neural Networks and Backpropagation Works/5. Gradient Descent.mp4

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1. How Neural Networks and Backpropagation Works/6. The Forward Propagation-en_US.srt

13.77KB

1. How Neural Networks and Backpropagation Works/6. The Forward Propagation.mp4

52.23MB

1. How Neural Networks and Backpropagation Works/7. Backpropagation Part 1-en_US.srt

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1. How Neural Networks and Backpropagation Works/7. Backpropagation Part 1.mp4

29.37MB

1. How Neural Networks and Backpropagation Works/8. Backpropagation Part 2-en_US.srt

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1. How Neural Networks and Backpropagation Works/8. Backpropagation Part 2.mp4

27.82MB

1. How Neural Networks and Backpropagation Works/BEFORE STARTING...PLEASE READ THIS.html

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1. How Neural Networks and Backpropagation Works/Before Proceeding with the Backpropagation.html

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10. Visualize the Learning Process/1. Visualize Learning Part 1-en_US.srt

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10. Visualize the Learning Process/7. Neural Networks Playground-en_US.srt

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10. Visualize the Learning Process/7. Neural Networks Playground.mp4

32.52MB

11. Implementing a Neural Network from Scratch with Numpy/1. The Dataset and Hyperparameters-en_US.srt

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11. Implementing a Neural Network from Scratch with Numpy/1. The Dataset and Hyperparameters.mp4

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11. Implementing a Neural Network from Scratch with Numpy/2. Understanding the Implementation-en_US.srt

10.9KB

11. Implementing a Neural Network from Scratch with Numpy/2. Understanding the Implementation.mp4

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11. Implementing a Neural Network from Scratch with Numpy/3. Forward Propagation-en_US.srt

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11. Implementing a Neural Network from Scratch with Numpy/4. Loss Function-en_US.srt

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11. Implementing a Neural Network from Scratch with Numpy/4. Loss Function.mp4

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11. Implementing a Neural Network from Scratch with Numpy/5. Prediction-en_US.srt

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11. Implementing a Neural Network from Scratch with Numpy/6. Backpropagation Equations-en_US.srt

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11. Implementing a Neural Network from Scratch with Numpy/6. Backpropagation Equations.mp4

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11. Implementing a Neural Network from Scratch with Numpy/7. Backpropagation-en_US.srt

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11. Implementing a Neural Network from Scratch with Numpy/7. Backpropagation.mp4

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11. Implementing a Neural Network from Scratch with Numpy/8. Initializing the Network-en_US.srt

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11. Implementing a Neural Network from Scratch with Numpy/8. Initializing the Network.mp4

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11. Implementing a Neural Network from Scratch with Numpy/9. Training the Model-en_US.srt

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11. Implementing a Neural Network from Scratch with Numpy/9. Training the Model.mp4

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11. Implementing a Neural Network from Scratch with Numpy/Notebook for the following Lecture.html

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12. Practical Neural Networks in PyTorch - Application 2 Handwritten Digits/1. Code Details-en_US.srt

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12. Practical Neural Networks in PyTorch - Application 2 Handwritten Digits/1. Code Details.mp4

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12. Practical Neural Networks in PyTorch - Application 2 Handwritten Digits/2. Importing and Defining Parameters-en_US.srt

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12. Practical Neural Networks in PyTorch - Application 2 Handwritten Digits/2. Importing and Defining Parameters.mp4

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12. Practical Neural Networks in PyTorch - Application 2 Handwritten Digits/3. Defining the Network Class-en_US.srt

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12. Practical Neural Networks in PyTorch - Application 2 Handwritten Digits/3. Defining the Network Class.mp4

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12. Practical Neural Networks in PyTorch - Application 2 Handwritten Digits/4. Creating the network class and the network functions-en_US.srt

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12. Practical Neural Networks in PyTorch - Application 2 Handwritten Digits/5. Training the Network-en_US.srt

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12. Practical Neural Networks in PyTorch - Application 2 Handwritten Digits/5. Training the Network.mp4

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12. Practical Neural Networks in PyTorch - Application 2 Handwritten Digits/6. Testing the Network-en_US.srt

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12. Practical Neural Networks in PyTorch - Application 2 Handwritten Digits/6. Testing the Network.mp4

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12. Practical Neural Networks in PyTorch - Application 2 Handwritten Digits/The MNIST Dataset.html

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13. Convolutional Neural Networks/1. Prerequisite Filters-en_US.srt

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13. Convolutional Neural Networks/10. Important formulas-en_US.srt

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13. Convolutional Neural Networks/10. Important formulas.mp4

13.38MB

13. Convolutional Neural Networks/11. CNN Characteristics-en_US.srt

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13. Convolutional Neural Networks/11. CNN Characteristics.mp4

45.88MB

13. Convolutional Neural Networks/12. Regularization and Batch Normalization in CNNs-en_US.srt

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13. Convolutional Neural Networks/12. Regularization and Batch Normalization in CNNs.mp4

18.19MB

13. Convolutional Neural Networks/13. DropBlock Dropout in CNNs-en_US.srt

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13. Convolutional Neural Networks/13. DropBlock Dropout in CNNs.mp4

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13. Convolutional Neural Networks/14. Softmax with Temperature-en_US.srt

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27.35MB

13. Convolutional Neural Networks/2. Introduction to Convolutional Networks and the need for them-en_US.srt

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13. Convolutional Neural Networks/2. Introduction to Convolutional Networks and the need for them.mp4

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13. Convolutional Neural Networks/3. Filters and Features-en_US.srt

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13. Convolutional Neural Networks/3. Filters and Features.mp4

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13. Convolutional Neural Networks/4. Convolution over Volume Animation-en_US.srt

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13. Convolutional Neural Networks/4. Convolution over Volume Animation.mp4

21.31MB

13. Convolutional Neural Networks/5. More on Convolutions-en_US.srt

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13. Convolutional Neural Networks/5. More on Convolutions.mp4

29.98MB

13. Convolutional Neural Networks/6. Quiz Solution Discussion-en_US.srt

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13. Convolutional Neural Networks/6. Quiz Solution Discussion.mp4

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13. Convolutional Neural Networks/7. A Tool for Convolution Visualization-en_US.srt

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13. Convolutional Neural Networks/7. A Tool for Convolution Visualization.mp4

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13. Convolutional Neural Networks/8. Activation, Pooling and FC-en_US.srt

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13. Convolutional Neural Networks/8. Activation, Pooling and FC.mp4

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13. Convolutional Neural Networks/9. CNN Visualization-en_US.srt

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13. Convolutional Neural Networks/9. CNN Visualization.mp4

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13. Convolutional Neural Networks/Convolution over Volume Animation Resource.html

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14. Practical Convolutional Networks in PyTorch - Image Classification/1. Loading and Normalizing the Dataset-en_US.srt

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14. Practical Convolutional Networks in PyTorch - Image Classification/1. Loading and Normalizing the Dataset.mp4

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14. Practical Convolutional Networks in PyTorch - Image Classification/10. Classifying your own Handwritten images-en_US.srt

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14. Practical Convolutional Networks in PyTorch - Image Classification/10. Classifying your own Handwritten images.mp4

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14. Practical Convolutional Networks in PyTorch - Image Classification/2. Visualizing and Loading the Dataset-en_US.srt

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14. Practical Convolutional Networks in PyTorch - Image Classification/2. Visualizing and Loading the Dataset.mp4

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14. Practical Convolutional Networks in PyTorch - Image Classification/3. Building the CNN-en_US.srt

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14. Practical Convolutional Networks in PyTorch - Image Classification/3. Building the CNN.mp4

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14. Practical Convolutional Networks in PyTorch - Image Classification/4. Defining the Model-en_US.srt

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14. Practical Convolutional Networks in PyTorch - Image Classification/4. Defining the Model.mp4

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14. Practical Convolutional Networks in PyTorch - Image Classification/5. Understanding the Propagation-en_US.srt

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14. Practical Convolutional Networks in PyTorch - Image Classification/5. Understanding the Propagation.mp4

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14. Practical Convolutional Networks in PyTorch - Image Classification/6. Training the CNN-en_US.srt

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14. Practical Convolutional Networks in PyTorch - Image Classification/6. Training the CNN.mp4

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14. Practical Convolutional Networks in PyTorch - Image Classification/7. Testing the CNN-en_US.srt

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14. Practical Convolutional Networks in PyTorch - Image Classification/7. Testing the CNN.mp4

35.82MB

14. Practical Convolutional Networks in PyTorch - Image Classification/8. Plotting and Putting into Action-en_US.srt

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14. Practical Convolutional Networks in PyTorch - Image Classification/8. Plotting and Putting into Action.mp4

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14. Practical Convolutional Networks in PyTorch - Image Classification/9. Predicting an image-en_US.srt

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14. Practical Convolutional Networks in PyTorch - Image Classification/9. Predicting an image.mp4

17.46MB

15. CNN Architectures/1. CNN Architectures Part 1-en_US.srt

15.19KB

15. CNN Architectures/1. CNN Architectures Part 1.mp4

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15. CNN Architectures/2. Residual Networks Part 1-en_US.srt

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15. CNN Architectures/2. Residual Networks Part 1.mp4

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15. CNN Architectures/3. Residual Networks Part 2-en_US.srt

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15. CNN Architectures/4. CNN Architectures Part 2-en_US.srt

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15. CNN Architectures/4. CNN Architectures Part 2.mp4

13.38MB

15. CNN Architectures/5. Densely Connected Networks-en_US.srt

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15. CNN Architectures/5. Densely Connected Networks.mp4

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15. CNN Architectures/6. Squeeze-Excite Networks-en_US.srt

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15. CNN Architectures/6. Squeeze-Excite Networks.mp4

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15. CNN Architectures/7. Seperable Convolutions-en_US.srt

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15. CNN Architectures/7. Seperable Convolutions.mp4

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15. CNN Architectures/8. Transfer Learning-en_US.srt

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15. CNN Architectures/8. Transfer Learning.mp4

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15. CNN Architectures/Note on Residual Networks Implementation.html

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16. Practical Residual Networks in PyTorch/1. Practical ResNet Part 1-en_US.srt

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16. Practical Residual Networks in PyTorch/1. Practical ResNet Part 1.mp4

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16. Practical Residual Networks in PyTorch/2. Practical ResNet Part 2-en_US.srt

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16. Practical Residual Networks in PyTorch/3. Practical ResNet Part 3-en_US.srt

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16. Practical Residual Networks in PyTorch/3. Practical ResNet Part 3.mp4

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16. Practical Residual Networks in PyTorch/4. Practical ResNet Part 4-en_US.srt

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16. Practical Residual Networks in PyTorch/4. Practical ResNet Part 4.mp4

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17. Transposed Convolutions/1. Introduction to Transposed Convolutions-en_US.srt

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17. Transposed Convolutions/2. Convolution Operation as Matrix Multiplication-en_US.srt

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17. Transposed Convolutions/2. Convolution Operation as Matrix Multiplication.mp4

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17. Transposed Convolutions/3. Transposed Convolutions.mp4

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18. Transfer Learning in PyTorch - Image Classification/1. Data Augmentation-en_US.srt

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18. Transfer Learning in PyTorch - Image Classification/1. Data Augmentation.mp4

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18. Transfer Learning in PyTorch - Image Classification/2. External URLs.txt

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18. Transfer Learning in PyTorch - Image Classification/2. Loading the Dataset-en_US.srt

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18. Transfer Learning in PyTorch - Image Classification/4. Understanding the data.mp4

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