|
Please note that this page does not hosts or makes available any of the listed filenames. You
cannot download any of those files from here.
|
| [TGx]Downloaded from torrentgalaxy.to .txt |
585B |
| 0 |
67.25KB |
| 01-Chapter 1 What is deep learning.mp4 |
76.79MB |
| 02-Chapter 1 Learning rules and representations from data.mp4 |
83.36MB |
| 03-Chapter 1 Understanding how deep learning works, in three figures.mp4 |
102.93MB |
| 04-Chapter 1 Before deep learning - A brief history of machine learning.mp4 |
82.65MB |
| 05-Chapter 1 Back to neural networks.mp4 |
77.93MB |
| 06-Chapter 1 Why deep learning Why now.mp4 |
56.47MB |
| 07-Chapter 1 Algorithms.mp4 |
62.35MB |
| 08-Chapter 2 The mathematical building blocks of neural networks.mp4 |
52.03MB |
| 09-Chapter 2 Data representations for neural networks.mp4 |
47.57MB |
| 1 |
240.01KB |
| 10 |
520.29KB |
| 10-Chapter 2 Real-world examples of data tensors.mp4 |
48.57MB |
| 11 |
180.40KB |
| 11-Chapter 2 The gears of neural networks - Tensor operations.mp4 |
46.50MB |
| 12 |
403.53KB |
| 12-Chapter 2 Tensor reshaping.mp4 |
36.72MB |
| 13 |
804.37KB |
| 13-Chapter 2 The engine of neural networks - Gradient-based optimization.mp4 |
49.96MB |
| 14 |
71.86KB |
| 14-Chapter 2 Derivative of a tensor operation - The gradient.mp4 |
69.46MB |
| 15 |
212.96KB |
| 15-Chapter 2 Chaining derivatives - The Backpropagation algorithm.mp4 |
55.02MB |
| 16 |
51.61KB |
| 16-Chapter 2 Looking back at our first example.mp4 |
53.70MB |
| 17 |
965.69KB |
| 17-Chapter 3 Introduction to Keras and TensorFlow.mp4 |
67.58MB |
| 18 |
623.69KB |
| 18-Chapter 3 Setting up a deep learning workspace.mp4 |
43.54MB |
| 19 |
712.98KB |
| 19-Chapter 3 First steps with TensorFlow.mp4 |
69.16MB |
| 2 |
942.96KB |
| 20 |
470.20KB |
| 20-Chapter 3 Anatomy of a neural network - Understanding core Keras APIs.mp4 |
56.10MB |
| 21 |
483.84KB |
| 21-Chapter 3 The “compile” step - Configuring the learning process.mp4 |
68.01MB |
| 22 |
291.13KB |
| 22-Chapter 4 Getting started with neural networks - Classification and regression.mp4 |
53.42MB |
| 23 |
469.29KB |
| 23-Chapter 4 Building your model.mp4 |
64.19MB |
| 24 |
135.48KB |
| 24-Chapter 4 Classifying newswires - A multiclass classification example.mp4 |
56.83MB |
| 25 |
496.95KB |
| 25-Chapter 4 Predicting house prices - A regression example.mp4 |
61.83MB |
| 26 |
547.91KB |
| 26-Chapter 5 Fundamentals of machine learning.mp4 |
56.96MB |
| 27 |
657.34KB |
| 27-Chapter 5 The nature of generalization in deep learning.mp4 |
80.49MB |
| 28 |
857.24KB |
| 28-Chapter 5 Evaluating machine learning models.mp4 |
72.53MB |
| 29 |
1012.92KB |
| 29-Chapter 5 Improving model fit.mp4 |
40.50MB |
| 3 |
878.90KB |
| 30 |
107.12KB |
| 30-Chapter 5 Improving generalization.mp4 |
69.36MB |
| 31 |
425.25KB |
| 31-Chapter 5 Regularizing your model.mp4 |
60.78MB |
| 32 |
933.44KB |
| 32-Chapter 6 The universal workflow of machine learning.mp4 |
66.92MB |
| 33 |
84.42KB |
| 33-Chapter 6 Collect a dataset.mp4 |
85.08MB |
| 34 |
22.81KB |
| 34-Chapter 6 Develop a model.mp4 |
44.39MB |
| 35 |
908.00KB |
| 35-Chapter 6 Beat a baseline.mp4 |
41.15MB |
| 36 |
113.35KB |
| 36-Chapter 6 Deploy the model.mp4 |
78.21MB |
| 37 |
680.13KB |
| 37-Chapter 6 Monitor your model in the wild.mp4 |
35.09MB |
| 38 |
829.96KB |
| 38-Chapter 7 Working with Keras - A deep dive.mp4 |
69.87MB |
| 39 |
442.40KB |
| 39-Chapter 7 Subclassing the Model class.mp4 |
35.13MB |
| 4 |
659.96KB |
| 40 |
19.64KB |
| 40-Chapter 7 Using built-in training and evaluation loops.mp4 |
60.17MB |
| 41 |
505.60KB |
| 41-Chapter 7 Writing your own training and evaluation loops.mp4 |
45.80MB |
| 42 |
660.75KB |
| 42-Chapter 7 Make it fast with tf.function.mp4 |
35.99MB |
| 43 |
174.24KB |
| 43-Chapter 8 Introduction to deep learning for computer vision.mp4 |
40.65MB |
| 44 |
344.74KB |
| 44-Chapter 8 The convolution operation.mp4 |
74.39MB |
| 45 |
225.68KB |
| 45-Chapter 8 Training a convnet from scratch on a small dataset.mp4 |
67.09MB |
| 46 |
741.62KB |
| 46-Chapter 8 Data preprocessing.mp4 |
61.66MB |
| 47 |
850.94KB |
| 47-Chapter 8 Leveraging a pretrained model.mp4 |
65.11MB |
| 48 |
93.12KB |
| 48-Chapter 8 Feature extraction with a pretrained model.mp4 |
64.34MB |
| 49 |
153.77KB |
| 49-Chapter 9 Advanced deep learning for computer vision.mp4 |
99.77MB |
| 5 |
353.91KB |
| 50 |
89.95KB |
| 50-Chapter 9 Modern convnet architecture patterns.mp4 |
58.74MB |
| 51 |
264.11KB |
| 51-Chapter 9 Residual connections.mp4 |
57.35MB |
| 52 |
494.91KB |
| 52-Chapter 9 Depthwise separable convolutions.mp4 |
67.90MB |
| 53 |
553.28KB |
| 53-Chapter 9 Interpreting what convnets learn.mp4 |
58.52MB |
| 54 |
117.90KB |
| 54-Chapter 9 Visualizing convnet filters.mp4 |
40.41MB |
| 55 |
640.69KB |
| 55-Chapter 9 Visualizing heatmaps of class activation.mp4 |
74.30MB |
| 56 |
665.93KB |
| 56-Chapter 10 Deep learning for timeseries.mp4 |
53.89MB |
| 57 |
41.91KB |
| 57-Chapter 10 Preparing the data.mp4 |
46.98MB |
| 58 |
179.07KB |
| 58-Chapter 10 Let’s try a basic machine learning model.mp4 |
45.05MB |
| 59 |
544.05KB |
| 59-Chapter 10 Understanding recurrent neural networks.mp4 |
40.46MB |
| 6 |
109.55KB |
| 60 |
883.05KB |
| 60-Chapter 10 A recurrent layer in Keras.mp4 |
41.66MB |
| 61 |
919.67KB |
| 61-Chapter 10 Advanced use of recurrent neural networks.mp4 |
59.85MB |
| 62 |
199.31KB |
| 62-Chapter 10 Using bidirectional RNNs.mp4 |
64.89MB |
| 63 |
1003.89KB |
| 63-Chapter 11 Deep learning for text.mp4 |
57.88MB |
| 64 |
110.17KB |
| 64-Chapter 11 Preparing text data.mp4 |
46.48MB |
| 65 |
307.35KB |
| 65-Chapter 11 Vocabulary indexing.mp4 |
50.36MB |
| 66 |
395.28KB |
| 66-Chapter 11 Two approaches for representing groups of words - Sets and sequences.mp4 |
79.82MB |
| 67 |
517.84KB |
| 67-Chapter 11 Processing words as a sequence - The sequence model approach, Part 1.mp4 |
70.54MB |
| 68 |
588.99KB |
| 68-Chapter 11 Processing words as a sequence - The sequence model approach, Part 2.mp4 |
52.54MB |
| 69 |
466.61KB |
| 69-Chapter 11 The Transformer architecture.mp4 |
71.72MB |
| 7 |
858.51KB |
| 70 |
991.60KB |
| 70-Chapter 11 The Transformer encoder.mp4 |
72.54MB |
| 71 |
657.80KB |
| 71-Chapter 11 Beyond text classification - Sequence-to-sequence learning.mp4 |
79.61MB |
| 72 |
40.13KB |
| 72-Chapter 11 Sequence-to-sequence learning with Transformer.mp4 |
56.14MB |
| 73 |
435.98KB |
| 73-Chapter 12 Generative deep learning.mp4 |
80.58MB |
| 74 |
117.04KB |
| 74-Chapter 12 How do you generate sequence data.mp4 |
81.89MB |
| 75 |
445.28KB |
| 75-Chapter 12 A text-generation callback with variable-temperature sampling.mp4 |
58.46MB |
| 76 |
24.25KB |
| 76-Chapter 12 DeepDream.mp4 |
57.37MB |
| 77 |
512.38KB |
| 77-Chapter 12 Neural style transfer.mp4 |
80.93MB |
| 78 |
528.86KB |
| 78-Chapter 12 Generating images with variational autoencoders.mp4 |
55.81MB |
| 79 |
208.61KB |
| 79-Chapter 12 Implementing a VAE with Keras.mp4 |
75.95MB |
| 8 |
67.45KB |
| 80 |
688.57KB |
| 80-Chapter 12 A bag of tricks.mp4 |
62.51MB |
| 81 |
977.49KB |
| 81-Chapter 13 Best practices for the real world.mp4 |
62.98MB |
| 82 |
624.95KB |
| 82-Chapter 13 Hyperparameter optimization.mp4 |
75.06MB |
| 83 |
473.27KB |
| 83-Chapter 13 Scaling-up model training.mp4 |
53.61MB |
| 84 |
343.28KB |
| 84-Chapter 13 Multi-GPU training.mp4 |
37.54MB |
| 85 |
429.12KB |
| 85-Chapter 13 TPU training.mp4 |
41.58MB |
| 86 |
866.41KB |
| 86-Chapter 14 Conclusions.mp4 |
81.16MB |
| 87 |
355.80KB |
| 87-Chapter 14 Key enabling technologies.mp4 |
63.57MB |
| 88 |
508.32KB |
| 88-Chapter 14 Key network architectures.mp4 |
59.91MB |
| 89 |
556.40KB |
| 89-Chapter 14 The limitations of deep learning.mp4 |
60.28MB |
| 9 |
429.98KB |
| 90 |
606.43KB |
| 90-Chapter 14 Local generalization vs. extreme generalization.mp4 |
45.33MB |
| 91 |
468.29KB |
| 91-Chapter 14 The purpose of intelligence.mp4 |
53.49MB |
| 92 |
289.96KB |
| 92-Chapter 14 Setting the course toward greater generality in AI.mp4 |
69.51MB |
| 93 |
11.40KB |
| 93-Chapter 14 Implementing intelligence - The missing ingredients.mp4 |
65.98MB |
| 94 |
887.20KB |
| 94-Chapter 14 The missing half of the picture.mp4 |
47.89MB |
| 95-Chapter 14 Blending together deep learning and program synthesis.mp4 |
58.91MB |
| 96-Chapter 14 Lifelong learning and modular subroutine reuse.mp4 |
84.14MB |
| TutsNode.com.txt |
63B |