[CourseClub.NET] Packtpub - Introduction to Deep Learning with Caffe2

Torrent Hash:
DBE98BABFA8886A285B5313E9BBFEBBC44595542
Number of Files:
32
Content Size:
988.39MB
Convert On:
2018-10-02
Magnet Link:
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File Name
Size
1.Setting Up Caffe2/01.The Course Overview.mp4
24.79MB
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1.Setting Up Caffe2/02.Set Up Caffe2 on Linux.mp4
16.53MB
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1.Setting Up Caffe2/03.Understanding the Caffe2 Architecture.mp4
22.01MB
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1.Setting Up Caffe2/04.Transitioning from Machine Learning to Deep Learning.mp4
32.48MB
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1.Setting Up Caffe2/05.Running an Image Classifier Using Caffe2.mp4
97.34MB
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2.Implementing Neural Networks and Deep Learning/06.Learn about Matrices Using Python – NumPy.mp4
56.91MB
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2.Implementing Neural Networks and Deep Learning/07.Understanding and Implementing Logistic Regression and Neural Networks.mp4
18.2MB
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2.Implementing Neural Networks and Deep Learning/08.Understanding and Implementing Deep Neural Networks.mp4
20.29MB
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3.Understanding Caffe2/09.Caffe2 Introduction.mp4
15.3MB
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3.Understanding Caffe2/10.Caffe2 Python Wrapper.mp4
39.03MB
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3.Understanding Caffe2/11.Mathematical Operators in Caffe2.mp4
27.64MB
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3.Understanding Caffe2/12.Network Creators and Assisters in Caffe2 – Part 1.mp4
18.51MB
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3.Understanding Caffe2/13.Network Creators and Assisters in Caffe2 – Part 2.mp4
21.56MB
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3.Understanding Caffe2/14.Network Creators and Assisters in Caffe2 – Part 3.mp4
14.44MB
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4.Understanding a Convolutional Neural Network/15.How Machines Learn to See!.mp4
24.31MB
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4.Understanding a Convolutional Neural Network/16.Introduction to Convolutional Neural Networks.mp4
27.86MB
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4.Understanding a Convolutional Neural Network/17.Implement a Convolution Layer Using Caffe2.mp4
32.52MB
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4.Understanding a Convolutional Neural Network/18.Pooling Layer and Dropout in Caffe2.mp4
79.01MB
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4.Understanding a Convolutional Neural Network/19.Role of Activation Functions in Solving Non-Linear Optimization.mp4
57.37MB
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5.Implementing Weight Initialization, Optimization, and Regularization/20.Machine Learning Strategy.mp4
9.68MB
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5.Implementing Weight Initialization, Optimization, and Regularization/21.How to Perform Data Selection, Preparation, and Processing.mp4
31.53MB
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5.Implementing Weight Initialization, Optimization, and Regularization/22.Regularization of Neural Networks.mp4
25.38MB
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5.Implementing Weight Initialization, Optimization, and Regularization/23.Optimizing Neural Networks.mp4
24.07MB
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5.Implementing Weight Initialization, Optimization, and Regularization/24.Optimization Algorithms.mp4
34.48MB
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6.Introduction to Recurrent Neural Network/25.Sequence Learning.mp4
17.61MB
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6.Introduction to Recurrent Neural Network/26.Introduction to Recurrent Neural Networks.mp4
16.08MB
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6.Introduction to Recurrent Neural Network/27.LSTMs – A Special Case of RNNs.mp4
42.03MB
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6.Introduction to Recurrent Neural Network/28.Learning about Word Embeddings.mp4
56.52MB
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6.Introduction to Recurrent Neural Network/29.Introduction to Augmented Recurrent Neural Networks.mp4
58.47MB
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Exercise Files/code_34511.zip
26.44MB
[CourseClub.NET].url
123B
[DesireCourse.Com].url
51B

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