|
RAR-files |
| packt.hands.on.deep.learning.with.tensorflow.2.0-analytics.rar |
50,000,000 |
815E73F1 |
| packt.hands.on.deep.learning.with.tensorflow.2.0-analytics.r00 |
50,000,000 |
36E74EA0 |
| packt.hands.on.deep.learning.with.tensorflow.2.0-analytics.r01 |
50,000,000 |
2D9A1BDE |
| packt.hands.on.deep.learning.with.tensorflow.2.0-analytics.r02 |
50,000,000 |
52963E0A |
| packt.hands.on.deep.learning.with.tensorflow.2.0-analytics.r03 |
50,000,000 |
2B453DB2 |
| packt.hands.on.deep.learning.with.tensorflow.2.0-analytics.r04 |
50,000,000 |
CF9BB37B |
| packt.hands.on.deep.learning.with.tensorflow.2.0-analytics.r05 |
50,000,000 |
CD8F1530 |
| packt.hands.on.deep.learning.with.tensorflow.2.0-analytics.r06 |
50,000,000 |
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| packt.hands.on.deep.learning.with.tensorflow.2.0-analytics.r07 |
50,000,000 |
9EC5E8CE |
| packt.hands.on.deep.learning.with.tensorflow.2.0-analytics.r08 |
50,000,000 |
52380793 |
| packt.hands.on.deep.learning.with.tensorflow.2.0-analytics.r09 |
29,613,686 |
C6D66560 |
|
| Total size: |
529,613,686 |
|
|
| Archived
files |
|
Architecture of CNNs-110677.mp4
[c9e79e46200590df]
|
42,333,713 |
0AA82B9A |
|
Case-Study on Improving Stock Price Prediction Using LSTM-110681.mp4
[504f2b271bccfc4d]
|
56,243,957 |
E4689AE3 |
|
Churn Prediction Model on Banking Data-110666.mp4
[98f4a06438463eb1]
|
18,372,168 |
74C1D3DE |
|
Data Wrangling and Data Normalization-110667.mp4
[79b2922f4387f3ca]
|
21,848,961 |
69A5DD64 |
|
Defining Our Neural Network Architecture-110668.mp4
[523db2282e9676a]
|
19,603,634 |
24420DD6 |
|
Hands-On Experience on Eager Execution-110672.mp4
[32da64c49c86550c]
|
9,226,154 |
67BBC2E6 |
|
Introduction to Convolutional Neural Networks-110675.mp4
[b30fc79beb9f8090]
|
10,223,744 |
F6F4B172 |
|
Introduction to LSTM-110680.mp4
[344d162d793a3a2c]
|
18,990,577 |
F969B075 |
|
Introduction to Recurrent Neural Networks-110679.mp4
[ba8345a25e316950]
|
33,147,658 |
7018865A |
|
Introduction to TensorBoard-110691.mp4
[21c5e70443d6a927]
|
13,831,176 |
6294C1B2 |
|
Introduction to Transfer Learning-110687.mp4
[4f554765dc51ec3]
|
25,089,513 |
478F63E5 |
|
Key Concepts-110664.mp4
[8a454d7e72f108e0]
|
9,584,918 |
7B2617FB |
|
Layers in ConvNets-110676.mp4
[86187b0433b8e458]
|
32,212,664 |
D86A8E2E |
|
Neural Machine Translation-110683.mp4
[210b2f3c6543a2b6]
|
24,528,223 |
F7734E59 |
|
Setting Up the Environment-110663.mp4
[f3cec64456fc5a07]
|
2,509,695 |
79F2675C |
|
Tensor2Tensor Using MNIST Dataset-110684.mp4
[965d8b8afe0191fa]
|
20,811,675 |
C45ECBE2 |
|
The Course Overview-110661.mp4
[6e31e21a41705359]
|
15,581,971 |
5D5F8F1D |
|
Training and Testing Neural Network for Object Detection-110689.mp4
[7aeff8c6755b6c7a]
|
52,001,212 |
B48867D1 |
|
Training and Testing Neural Network for Sentiment Analysis on IMDB Dataset-110688.mp4
[613debfe607b2dfe]
|
42,315,229 |
F9B50290 |
|
Training a Neural Network-110669.mp4
[7a29e8b50fb8136e]
|
6,362,662 |
817783A8 |
|
Variable Sharing-110673.mp4
[576b8e3487f71611]
|
29,032,692 |
152C9168 |
|
What are Neural Networks and Types of Neural Networks-110662.mp4
[1c21af99ed173a47]
|
8,112,522 |
4DB4689B |
|
What is Churn Prediction-110665.mp4
[298174fbd044cf08]
|
8,503,031 |
6CD29BBF |
|
What Is Eager Execution-110671.mp4
[9789bc0a7f765801]
|
9,142,798 |
6473199D |
|
| Total size: |
529,610,547 |
|
|
