Deep learning of wheat-machine learning Algorithm Advanced Step

Deep learning of wheat-machine learning Algorithm Advanced Step

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cp1933-Deep Learning Advanced Algorithm Combat

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This course, as the second stage of the Deep Learning series, introduces the basic concepts, principles, and common algorithms (such as decision trees, support vector machines, neural network algorithms, etc.) of machine learning. The Python language is used as a tool to illustrate each of these algorithms in conjunction with an example. After completing this course, students will understand the common algorithmic principles of machine learning and will use the relevant package in Python to perform data preprocessing, classification, and regression analysis of actual problems. It lays the necessary foundation for the development of machine learning related applications, and also lays the necessary foundation for learning advanced courses in depth learning.

1. Basic Concept Clear version

2. General overview of package installation and environment configuration

3. Environment Configuration Division Detailed

4. Environment Configuration Division under the detailed

5. Handwritten digit recognition

6. Neural network basic structure and gradient descent algorithm

7. Random Gradient descent algorithm

8. The gradient descent algorithm is implemented

9. The gradient descent algorithm realizes

10. Neural network handwritten digital demo

On the 11.Backpropagation algorithm

Under 12.Backpropagation algorithm

13.Backpropagation Algorithm Implementation

14.cross-entropy function

15.Softmax and Overfitting

16.Regulization

17.Regulazition and dropout

18. Normal distribution and initialization (fixed version)

19. Improved version of handwritten digital recognition implementation

20. Neural network parameter Hyper-parameters selection

21. Difficulties in deep neural networks

22. Use Rel to solve vanishinggradient problem

23.ConvolutionNerualNetwork algorithm

24.ConvolutionNeuralNetwork Implementation on

25.ConvolutionNeuralNetwork implementation of

26.Restricted Boltzmann Machine

27.Restricted Boltzmann Machine under

28.Deep Brief Network and Autoencoder

Deep Learning machine Learning algorithm Practical Python Advanced

Deep learning of wheat-machine learning Algorithm Advanced Step