CourseClub NET Packtpub - Introduction to Deep Learning with Caffe2

1. 1.Setting Up Caffe2/01.The Course Overview.mp424.79MB
2. 1.Setting Up Caffe2/02.Set Up Caffe2 on Linux.mp416.53MB
3. 1.Setting Up Caffe2/03.Understanding the Caffe2 Architecture.mp422.01MB
4. 1.Setting Up Caffe2/04.Transitioning from Machine Learning to Deep Learning.mp432.48MB
5. 1.Setting Up Caffe2/05.Running an Image Classifier Using Caffe2.mp497.34MB
6. 2.Implementing Neural Networks and Deep Learning/06.Learn about Matrices Using Python – NumPy.mp456.91MB
7. 2.Implementing Neural Networks and Deep Learning/07.Understanding and Implementing Logistic Regression and Neural Networks.mp418.2MB
8. 2.Implementing Neural Networks and Deep Learning/08.Understanding and Implementing Deep Neural Networks.mp420.29MB
9. 3.Understanding Caffe2/09.Caffe2 Introduction.mp415.3MB
10. 3.Understanding Caffe2/10.Caffe2 Python Wrapper.mp439.03MB
11. 3.Understanding Caffe2/11.Mathematical Operators in Caffe2.mp427.64MB
12. 3.Understanding Caffe2/12.Network Creators and Assisters in Caffe2 – Part 1.mp418.51MB
13. 3.Understanding Caffe2/13.Network Creators and Assisters in Caffe2 – Part 2.mp421.56MB
14. 3.Understanding Caffe2/14.Network Creators and Assisters in Caffe2 – Part 3.mp414.44MB
15. 4.Understanding a Convolutional Neural Network/15.How Machines Learn to See!.mp424.31MB
16. 4.Understanding a Convolutional Neural Network/16.Introduction to Convolutional Neural Networks.mp427.86MB
17. 4.Understanding a Convolutional Neural Network/17.Implement a Convolution Layer Using Caffe2.mp432.52MB
18. 4.Understanding a Convolutional Neural Network/18.Pooling Layer and Dropout in Caffe2.mp479.01MB
19. 4.Understanding a Convolutional Neural Network/19.Role of Activation Functions in Solving Non-Linear Optimization.mp457.37MB
20. 5.Implementing Weight Initialization, Optimization, and Regularization/20.Machine Learning Strategy.mp49.68MB
21. 5.Implementing Weight Initialization, Optimization, and Regularization/21.How to Perform Data Selection, Preparation, and Processing.mp431.53MB
22. 5.Implementing Weight Initialization, Optimization, and Regularization/22.Regularization of Neural Networks.mp425.38MB
23. 5.Implementing Weight Initialization, Optimization, and Regularization/23.Optimizing Neural Networks.mp424.07MB
24. 5.Implementing Weight Initialization, Optimization, and Regularization/24.Optimization Algorithms.mp434.48MB
25. 6.Introduction to Recurrent Neural Network/25.Sequence Learning.mp417.61MB
26. 6.Introduction to Recurrent Neural Network/26.Introduction to Recurrent Neural Networks.mp416.08MB
27. 6.Introduction to Recurrent Neural Network/27.LSTMs – A Special Case of RNNs.mp442.03MB
28. 6.Introduction to Recurrent Neural Network/28.Learning about Word Embeddings.mp456.52MB
29. 6.Introduction to Recurrent Neural Network/29.Introduction to Augmented Recurrent Neural Networks.mp458.47MB