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Home > Learning Deep Learning: Theory and Practice of Neural Networks, Computer Vision, Natural Language Processing, and Transformers Using TensorFlow

Learning Deep Learning: Theory and Practice of Neural Networks, Computer Vision, Natural Language Processing, and Transformers Using TensorFlow


Book Informaton

Learning Deep Learning: Theory and Practice of Neural Networks, Computer Vision, Natural Language Processing, and Transformers Using TensorFlow

Author

Magnus Ekman

Year of Publication

2021

Publisher

Addison-Wesley Professional

Pages

752

Language

en

ISBN

0137470355, 9780137470358

ARI Id

1673441895692


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Showing 1 to 20 of 291 entries
Chapters/HeadingsAuthor(s)PagesInfo
1 THE ROSENBLATT PERCEPTRON
Example of a Two-Input Perceptron
The Perceptron Learning Algorithm
Limitations of the Perceptron
Combining Multiple Perceptrons
Implementing Perceptrons with Linear Algebra
Vector Notation
Dot Product
Extending the Vector to a 2D Matrix
Matrix-Vector Multiplication
Matrix-Matrix Multiplication
Summary of Vector and Matrix Operations Used for Perceptrons
Dot Product as a Matrix Multiplication
Extending to Multidimensional Tensors
Geometric Interpretation of the Perceptron
Understanding the Bias Term
Concluding Remarks on the Perceptron
2 GRADIENT-BASED LEARNING
Intuitive Explanation of the Perceptron Learning Algorithm
Derivatives and Optimization Problems
Chapters/HeadingsAuthor(s)PagesInfo
Showing 1 to 20 of 291 entries
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