Deep Learning with Python Second Edition Video Edition | 37FF259D034DAE7D1CA7ABE40A73CDBAB6C8E90F

Deep Learning with Python Second Edition Video Edition

Name	Deep Learning with Python, Second Edition, Video Edition	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	6.2 GB
Total Files	193
Last Seen	2025-04-11 00:18
Hash	37FF259D034DAE7D1CA7ABE40A73CDBAB6C8E90F

/[TutsNode.com] - Deep Learning with Python, Second Edition, Video Edition/
03-Chapter 1 Understanding how deep learning works, in three figures.mp4	107.9 MB
49-Chapter 9 Advanced deep learning for computer vision.mp4	104.6 MB
33-Chapter 6 Collect a dataset.mp4	89.2 MB
96-Chapter 14 Lifelong learning and modular subroutine reuse.mp4	88.2 MB
02-Chapter 1 Learning rules and representations from data.mp4	87.4 MB
04-Chapter 1 Before deep learning - A brief history of machine learning.mp4	86.7 MB
74-Chapter 12 How do you generate sequence data.mp4	85.9 MB
86-Chapter 14 Conclusions.mp4	85.1 MB
77-Chapter 12 Neural style transfer.mp4	84.9 MB
73-Chapter 12 Generative deep learning.mp4	84.5 MB
27-Chapter 5 The nature of generalization in deep learning.mp4	84.4 MB
66-Chapter 11 Two approaches for representing groups of words - Sets and sequences.mp4	83.7 MB
71-Chapter 11 Beyond text classification - Sequence-to-sequence learning.mp4	83.5 MB
36-Chapter 6 Deploy the model.mp4	82.0 MB
05-Chapter 1 Back to neural networks.mp4	81.7 MB
01-Chapter 1 What is deep learning.mp4	80.5 MB
79-Chapter 12 Implementing a VAE with Keras.mp4	79.6 MB
82-Chapter 13 Hyperparameter optimization.mp4	78.7 MB
44-Chapter 8 The convolution operation.mp4	78.0 MB
55-Chapter 9 Visualizing heatmaps of class activation.mp4	77.9 MB
70-Chapter 11 The Transformer encoder.mp4	76.1 MB
28-Chapter 5 Evaluating machine learning models.mp4	76.1 MB
69-Chapter 11 The Transformer architecture.mp4	75.2 MB
67-Chapter 11 Processing words as a sequence - The sequence model approach, Part 1.mp4	74.0 MB
38-Chapter 7 Working with Keras - A deep dive.mp4	73.3 MB
92-Chapter 14 Setting the course toward greater generality in AI.mp4	72.9 MB
14-Chapter 2 Derivative of a tensor operation - The gradient.mp4	72.8 MB
30-Chapter 5 Improving generalization.mp4	72.7 MB
19-Chapter 3 First steps with TensorFlow.mp4	72.5 MB
21-Chapter 3 The “compile” step - Configuring the learning process.mp4	71.3 MB
52-Chapter 9 Depthwise separable convolutions.mp4	71.2 MB
17-Chapter 3 Introduction to Keras and TensorFlow.mp4	70.9 MB
45-Chapter 8 Training a convnet from scratch on a small dataset.mp4	70.3 MB
32-Chapter 6 The universal workflow of machine learning.mp4	70.2 MB
93-Chapter 14 Implementing intelligence - The missing ingredients.mp4	69.2 MB
47-Chapter 8 Leveraging a pretrained model.mp4	68.3 MB
62-Chapter 10 Using bidirectional RNNs.mp4	68.0 MB
48-Chapter 8 Feature extraction with a pretrained model.mp4	67.5 MB
23-Chapter 4 Building your model.mp4	67.3 MB
87-Chapter 14 Key enabling technologies.mp4	66.7 MB
81-Chapter 13 Best practices for the real world.mp4	66.0 MB
80-Chapter 12 A bag of tricks.mp4	65.5 MB
07-Chapter 1 Algorithms.mp4	65.4 MB
25-Chapter 4 Predicting house prices - A regression example.mp4	64.8 MB
46-Chapter 8 Data preprocessing.mp4	64.7 MB
31-Chapter 5 Regularizing your model.mp4	63.7 MB
89-Chapter 14 The limitations of deep learning.mp4	63.2 MB
40-Chapter 7 Using built-in training and evaluation loops.mp4	63.1 MB
88-Chapter 14 Key network architectures.mp4	62.8 MB
61-Chapter 10 Advanced use of recurrent neural networks.mp4	62.8 MB
95-Chapter 14 Blending together deep learning and program synthesis.mp4	61.8 MB
50-Chapter 9 Modern convnet architecture patterns.mp4	61.6 MB
53-Chapter 9 Interpreting what convnets learn.mp4	61.4 MB
75-Chapter 12 A text-generation callback with variable-temperature sampling.mp4	61.3 MB
63-Chapter 11 Deep learning for text.mp4	60.7 MB
76-Chapter 12 DeepDream.mp4	60.2 MB
51-Chapter 9 Residual connections.mp4	60.1 MB
26-Chapter 5 Fundamentals of machine learning.mp4	59.7 MB
24-Chapter 4 Classifying newswires - A multiclass classification example.mp4	59.6 MB
06-Chapter 1 Why deep learning Why now.mp4	59.2 MB
72-Chapter 11 Sequence-to-sequence learning with Transformer.mp4	58.9 MB
20-Chapter 3 Anatomy of a neural network - Understanding core Keras APIs.mp4	58.8 MB
78-Chapter 12 Generating images with variational autoencoders.mp4	58.5 MB
15-Chapter 2 Chaining derivatives - The Backpropagation algorithm.mp4	57.7 MB
56-Chapter 10 Deep learning for timeseries.mp4	56.5 MB
16-Chapter 2 Looking back at our first example.mp4	56.3 MB
83-Chapter 13 Scaling-up model training.mp4	56.2 MB
91-Chapter 14 The purpose of intelligence.mp4	56.1 MB
22-Chapter 4 Getting started with neural networks - Classification and regression.mp4	56.0 MB
68-Chapter 11 Processing words as a sequence - The sequence model approach, Part 2.mp4	55.1 MB
08-Chapter 2 The mathematical building blocks of neural networks.mp4	54.6 MB
65-Chapter 11 Vocabulary indexing.mp4	52.8 MB
13-Chapter 2 The engine of neural networks - Gradient-based optimization.mp4	52.4 MB
10-Chapter 2 Real-world examples of data tensors.mp4	50.9 MB
94-Chapter 14 The missing half of the picture.mp4	50.2 MB
09-Chapter 2 Data representations for neural networks.mp4	49.9 MB
57-Chapter 10 Preparing the data.mp4	49.3 MB
11-Chapter 2 The gears of neural networks - Tensor operations.mp4	48.8 MB
64-Chapter 11 Preparing text data.mp4	48.7 MB
41-Chapter 7 Writing your own training and evaluation loops.mp4	48.0 MB
90-Chapter 14 Local generalization vs. extreme generalization.mp4	47.5 MB
58-Chapter 10 Let’s try a basic machine learning model.mp4	47.2 MB
34-Chapter 6 Develop a model.mp4	46.5 MB
18-Chapter 3 Setting up a deep learning workspace.mp4	45.7 MB
60-Chapter 10 A recurrent layer in Keras.mp4	43.7 MB
85-Chapter 13 TPU training.mp4	43.6 MB
35-Chapter 6 Beat a baseline.mp4	43.2 MB
43-Chapter 8 Introduction to deep learning for computer vision.mp4	42.6 MB
29-Chapter 5 Improving model fit.mp4	42.5 MB
59-Chapter 10 Understanding recurrent neural networks.mp4	42.4 MB
54-Chapter 9 Visualizing convnet filters.mp4	42.4 MB
84-Chapter 13 Multi-GPU training.mp4	39.4 MB
12-Chapter 2 Tensor reshaping.mp4	38.5 MB
42-Chapter 7 Make it fast with tf.function.mp4	37.7 MB
39-Chapter 7 Subclassing the Model class.mp4	36.8 MB
37-Chapter 6 Monitor your model in the wild.mp4	36.8 MB
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