种子简介

种子名称： [FreeCoursesOnline.Me] PacktPub - Deep Learning with Real World Projects [Video]
文件类型： 视频
文件数目： 156个文件
文件大小： 7.03 GB
收录时间： 2020-1-27 11:51
已经下载： 3次
资源热度： 189
最近下载： 2024-11-16 09:07

下载BT种子文件

下载Torrent文件(.torrent) 立即下载

磁力链接下载

magnet:?xt=urn:btih:a6c470f088388a0cb7ba0c8ee31b8f13aefc0e97&dn=[FreeCoursesOnline.Me] PacktPub - Deep Learning with Real World Projects [Video] 复制链接到迅雷、QQ旋风进行下载，或者使用百度云离线下载。

喜欢这个种子的人也喜欢

种子包含的文件

[FreeCoursesOnline.Me] PacktPub - Deep Learning with Real World Projects [Video].torrent

1 - Introduction/Activation Functions.mp4151.3MB

1 - Introduction/Code Password.mp4719.85KB

1 - Introduction/History of Deep learning.mp481.44MB

1 - Introduction/Introduction.mp465.6MB

1 - Introduction/Multi-Level Perceptrons.mp481.52MB

1 - Introduction/Neural Network Playground.mp4152.12MB

1 - Introduction/Perceptrons.mp437.66MB

1 - Introduction/Representations.mp4158.08MB

1 - Introduction/Training Neural Network - Part 1.mp4122.56MB

1 - Introduction/Training Neural Network - Part 2.mp456.79MB

1 - Introduction/Training Neural Network - Part 3.mp4110.75MB

10 - CNN-Industry Live Project - Find..Save Life/Introduction.mp410.86MB

10 - CNN-Industry Live Project - Find..Save Life/Working with X-Ray images - Case Study - Part 1.mp49.03MB

10 - CNN-Industry Live Project - Find..Save Life/Working with X-Ray images - Case Study - Part 2.mp48.82MB

10 - CNN-Industry Live Project - Find..Save Life/Working with X-Ray images - Case Study - Part 3.mp414.09MB

10 - CNN-Industry Live Project - Find..Save Life/Working with X-Ray images - Case Study - Part 4.mp418.31MB

10 - CNN-Industry Live Project - Find..Save Life/Working with X-Ray images - Case Study - Part 5.mp426.57MB

10 - CNN-Industry Live Project - Find..Save Life/Working with X-Ray images - Case Study - Part 6.mp418.34MB

11 - Recurrent Neural Networks - Introduction/Architecture.mp422.48MB

11 - Recurrent Neural Networks - Introduction/Batch data.mp48.52MB

11 - Recurrent Neural Networks - Introduction/Introduction to RNN.mp413.47MB

11 - Recurrent Neural Networks - Introduction/One-to-Many.mp417.41MB

11 - Recurrent Neural Networks - Introduction/RNN - Part 1.mp49.87MB

11 - Recurrent Neural Networks - Introduction/RNN Formula.mp429.21MB

11 - Recurrent Neural Networks - Introduction/RNN Part 2.mp46.43MB

11 - Recurrent Neural Networks - Introduction/Simplified Notations.mp429.4MB

11 - Recurrent Neural Networks - Introduction/Training RNN.mp411.6MB

11 - Recurrent Neural Networks - Introduction/Types of RNN - Part 1.mp47.41MB

11 - Recurrent Neural Networks - Introduction/Types of RNN - Part 2.mp413.22MB

11 - Recurrent Neural Networks - Introduction/Vanishing Gradient.mp421.37MB

12 - Recurrent Neural Networks - LSTM/Bidirectional RNN.mp414.31MB

12 - Recurrent Neural Networks - LSTM/Gated Recurrent Network (GRU).mp427.03MB

12 - Recurrent Neural Networks - LSTM/Introduction.mp44.43MB

12 - Recurrent Neural Networks - LSTM/LSTM - Part 1.mp47.66MB

12 - Recurrent Neural Networks - LSTM/LSTM - Part 2.mp45.96MB

12 - Recurrent Neural Networks - LSTM/LSTM - Part 3.mp44.17MB

12 - Recurrent Neural Networks - LSTM/LSTM - Part 4.mp411.56MB

12 - Recurrent Neural Networks - LSTM/LSTM - Part 5.mp419.68MB

12 - Recurrent Neural Networks - LSTM/LSTM Equation.mp48.51MB

12 - Recurrent Neural Networks - LSTM/Online Offline Mode.mp410.25MB

13 - Recurrent Neutral Networks - Part-Of-Speech Tagger/Part-Of-Speech Tagger case- study (Part-2).mp487.66MB

13 - Recurrent Neutral Networks - Part-Of-Speech Tagger/Part-Of-Speech Tagger case- study (Part-3).mp442.59MB

13 - Recurrent Neutral Networks - Part-Of-Speech Tagger/Part-Of-Speech Tagger case- study (Part-4).mp457.08MB

13 - Recurrent Neutral Networks - Part-Of-Speech Tagger/Part-Of-Speech Tagger case- study (Part-5).mp4109.35MB

13 - Recurrent Neutral Networks - Part-Of-Speech Tagger/Part-Of-Speech Tagger case- study (Part-6).mp425.65MB

13 - Recurrent Neutral Networks - Part-Of-Speech Tagger/Part-Of-Speech Tagger case- study (Part-7).mp459.99MB

13 - Recurrent Neutral Networks - Part-Of-Speech Tagger/Part-Of-Speech Tagger case- study (Part-8).mp4120.05MB

13 - Recurrent Neutral Networks - Part-Of-Speech Tagger/Part-Of-Speech Tagger case- study (Part-9).mp430.86MB

13 - Recurrent Neutral Networks - Part-Of-Speech Tagger/Part-Of-Speech Tagger case-study (Part-1).mp456.18MB

14 - Text generation using RNN/Text Generation - Code generator case- study (Part-1).mp4171.29MB

14 - Text generation using RNN/Text Generation - Code generator case- study (Part-2).mp4105.19MB

14 - Text generation using RNN/Text Generation - Code generator case- study (Part-3).mp448.67MB

14 - Text generation using RNN/Text Generation - Code generator case- study (Part-4).mp440.03MB

2 - Artificial Neural Networks-Introduction/Activation Functions.mp441.88MB

2 - Artificial Neural Networks-Introduction/Assumptions in Neural Networks.mp445.8MB

2 - Artificial Neural Networks-Introduction/Deep Learning.mp428.97MB

2 - Artificial Neural Networks-Introduction/Example for Perceptron.mp444.98MB

2 - Artificial Neural Networks-Introduction/Homogeneous Co-ordinate.mp423.61MB

2 - Artificial Neural Networks-Introduction/Input Layer.mp453.57MB

2 - Artificial Neural Networks-Introduction/Introduction.mp423.91MB

2 - Artificial Neural Networks-Introduction/Multi Classifier.mp437.87MB

2 - Artificial Neural Networks-Introduction/Neural Networks.mp449.32MB

2 - Artificial Neural Networks-Introduction/Output Layer.mp414.07MB

2 - Artificial Neural Networks-Introduction/Perceptron for Classifiers.mp431.96MB

2 - Artificial Neural Networks-Introduction/Perceptron in Depth.mp430.71MB

2 - Artificial Neural Networks-Introduction/Perceptron.mp429.65MB

2 - Artificial Neural Networks-Introduction/Sigmoid function.mp426.53MB

2 - Artificial Neural Networks-Introduction/Training in Neural Networks.mp432.74MB

2 - Artificial Neural Networks-Introduction/Understanding Human Brain.mp426.64MB

2 - Artificial Neural Networks-Introduction/Understanding MNIST.mp420.44MB

2 - Artificial Neural Networks-Introduction/Understanding Notations.mp499.95MB

3 - ANN - Feed Forward Network/Bidirectional RNN.mp443.49MB

3 - ANN - Feed Forward Network/Introduction.mp450.45MB

3 - ANN - Feed Forward Network/Online Offline Mode.mp436.04MB

3 - ANN - Feed Forward Network/Pseudocode for Batch.mp428.82MB

3 - ANN - Feed Forward Network/Pseudocode.mp440.65MB

3 - ANN - Feed Forward Network/Understanding Dimensions.mp458.63MB

3 - ANN - Feed Forward Network/Vectorised Methods.mp481.39MB

4 - Back Propagation/Back Propagation Training - Part 1.mp446.54MB

4 - Back Propagation/Back Propagation Training - Part 10.mp423.04MB

4 - Back Propagation/Back Propagation Training - Part 2.mp438.07MB

4 - Back Propagation/Back Propagation Training - Part 3.mp414.74MB

4 - Back Propagation/Back Propagation Training - Part 4.mp434.74MB

4 - Back Propagation/Back Propagation Training - Part 5.mp434.76MB

4 - Back Propagation/Back Propagation Training - Part 6.mp423.3MB

4 - Back Propagation/Back Propagation Training - Part 7.mp420.59MB

4 - Back Propagation/Back Propagation Training - Part 8.mp427MB

4 - Back Propagation/Back Propagation Training - Part 9.mp428.96MB

4 - Back Propagation/Finding Global Minima.mp410.31MB

4 - Back Propagation/Introducing Loss Function.mp444.13MB

4 - Back Propagation/Introduction.mp435.37MB

4 - Back Propagation/Pseudocode.mp412.67MB

4 - Back Propagation/SGD.mp438.95MB

4 - Back Propagation/Sigmoid Function.mp425.96MB

4 - Back Propagation/Training for Batches.mp422.82MB

5 - Regularisation/Batch Normalisation - Part 1.mp436.08MB

5 - Regularisation/Batch Normalisation - Part 2.mp437.55MB

5 - Regularisation/Batch Normalisation - Part 3.mp450.64MB

5 - Regularisation/Dropouts Part 1.mp424.18MB

5 - Regularisation/Dropouts Part 2.mp413.46MB

5 - Regularisation/Introducing Keras.mp4122.91MB

5 - Regularisation/Introducing TensorFlow.mp445.42MB

5 - Regularisation/Introduction to Regularisation.mp449.04MB

6 - Convolution Neural Networks/Applications for CNN.mp454.5MB

6 - Convolution Neural Networks/Combining Network.mp453.18MB

6 - Convolution Neural Networks/Convolution - Part 1.mp443.4MB

6 - Convolution Neural Networks/Convolution - Part 2.mp479.49MB

6 - Convolution Neural Networks/Feature Map.mp4127.57MB

6 - Convolution Neural Networks/Formulas.mp418.56MB

6 - Convolution Neural Networks/Idea behind CNN - Part 1.mp445.92MB

6 - Convolution Neural Networks/Idea behind CNN - Part 2.mp475.88MB

6 - Convolution Neural Networks/Images.mp4161.11MB

6 - Convolution Neural Networks/Introduction.mp442.93MB

6 - Convolution Neural Networks/Padding.mp415.13MB

6 - Convolution Neural Networks/Pooling.mp470.59MB

6 - Convolution Neural Networks/Stride and Padding.mp434.19MB

6 - Convolution Neural Networks/Video.mp440MB

6 - Convolution Neural Networks/Weight and Bias.mp482.52MB

7 - CNN-Keras/Introduction.mp47.73MB

7 - CNN-Keras/Practical on CNN - Case Study - Part 1.mp410.29MB

7 - CNN-Keras/Practical on CNN - Case Study - Part 2.mp428.31MB

7 - CNN-Keras/Practical on CNN - Case Study - Part 3.mp436MB

7 - CNN-Keras/Practical on CNN - Case Study - Part 4.mp413.22MB

7 - CNN-Keras/Practical on CNN - Case Study - Part 5.mp47.5MB

7 - CNN-Keras/VGG16 (Visual Geometry Group).mp444.63MB

8 - CNN-Transfer Learning/AlexNet.mp473.82MB

8 - CNN-Transfer Learning/Analysis - Part 1.mp4109.77MB

8 - CNN-Transfer Learning/Analysis - Part 2.mp446.01MB

8 - CNN-Transfer Learning/Case Study - Part 1.mp4194.08MB

8 - CNN-Transfer Learning/Case Study - Part 2.mp495.9MB

8 - CNN-Transfer Learning/Case Study - Part 3.mp439.14MB

8 - CNN-Transfer Learning/GoogleNet.mp448.7MB

8 - CNN-Transfer Learning/Introduction.mp444.61MB

8 - CNN-Transfer Learning/ResNet - Part 1.mp432.3MB

8 - CNN-Transfer Learning/ResNet - Part 2.mp428.15MB

8 - CNN-Transfer Learning/Transfer Learning - Part 1.mp47.42MB

8 - CNN-Transfer Learning/Transfer Learning - Part 2.mp419.86MB

8 - CNN-Transfer Learning/Transfer Learning - Part 3.mp435.32MB

8 - CNN-Transfer Learning/Transfer Learning - Part 4.mp439.9MB

8 - CNN-Transfer Learning/Transfer Learning - Part 5.mp427.1MB

8 - CNN-Transfer Learning/Transfer Learning - Part 6.mp436.34MB

9 - CNN-Industry Live Project - Playing..Natural Images/Introduction.mp419.69MB

9 - CNN-Industry Live Project - Playing..Natural Images/Working with Flower Images - Case Study - Part 1.mp449.56MB

9 - CNN-Industry Live Project - Playing..Natural Images/Working with Flower Images - Case Study - Part 10.mp456.74MB

9 - CNN-Industry Live Project - Playing..Natural Images/Working with Flower Images - Case Study - Part 11.mp461.74MB

9 - CNN-Industry Live Project - Playing..Natural Images/Working with Flower Images - Case Study - Part 12.mp4159.46MB

9 - CNN-Industry Live Project - Playing..Natural Images/Working with Flower Images - Case Study - Part 13.mp431.75MB

9 - CNN-Industry Live Project - Playing..Natural Images/Working with Flower Images - Case Study - Part 14.mp475.11MB

9 - CNN-Industry Live Project - Playing..Natural Images/Working with Flower Images - Case Study - Part 2.mp4118.7MB

9 - CNN-Industry Live Project - Playing..Natural Images/Working with Flower Images - Case Study - Part 3.mp450.13MB

9 - CNN-Industry Live Project - Playing..Natural Images/Working with Flower Images - Case Study - Part 4.mp448.57MB

9 - CNN-Industry Live Project - Playing..Natural Images/Working with Flower Images - Case Study - Part 5.mp439.33MB

9 - CNN-Industry Live Project - Playing..Natural Images/Working with Flower Images - Case Study - Part 6.mp472.1MB

9 - CNN-Industry Live Project - Playing..Natural Images/Working with Flower Images - Case Study - Part 7.mp426.29MB

9 - CNN-Industry Live Project - Playing..Natural Images/Working with Flower Images - Case Study - Part 8.mp491.39MB

9 - CNN-Industry Live Project - Playing..Natural Images/Working with Flower Images - Case Study - Part 9.mp481.05MB