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MATLAB for Machine Learning

You're reading from   MATLAB for Machine Learning Unlock the power of deep learning for swift and enhanced results

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Product type Paperback
Published in Jan 2024
Publisher Packt
ISBN-13 9781835087695
Length 374 pages
Edition 2nd Edition
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Author (1):
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Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
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Toc

Table of Contents (17) Chapters Close

Preface 1. Part 1: Getting Started with Matlab
2. Chapter 1: Exploring MATLAB for Machine Learning FREE CHAPTER 3. Chapter 2: Working with Data in MATLAB 4. Part 2: Understanding Machine Learning Algorithms in MATLAB
5. Chapter 3: Prediction Using Classification and Regression 6. Chapter 4: Clustering Analysis and Dimensionality Reduction 7. Chapter 5: Introducing Artificial Neural Network Modeling 8. Chapter 6: Deep Learning and Convolutional Neural Networks 9. Part 3: Machine Learning in Practice
10. Chapter 7: Natural Language Processing Using MATLAB 11. Chapter 8: MATLAB for Image Processing and Computer Vision 12. Chapter 9: Time Series Analysis and Forecasting with MATLAB 13. Chapter 10: MATLAB Tools for Recommender Systems 14. Chapter 11: Anomaly Detection in MATLAB 15. Index 16. Other Books You May Enjoy

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

A

accuracy

improving, with Random Forest algorithm 326- 328

activation function 141, 143

exponential linear unit (ELU) function 142

hyperbolic tangent (Tanh) function 142

rectified linear unit (ReLU) function 142

sigmoid function 142

softmax function 142

step function 142

Adam optimization

exploring 175

Adaptive Boosting (AdaBoost) 232, 306

adaptive moment estimation (Adam) 174

Adaptive Synthetic Sampling (ADASYN) 289

adjusted R-squared 81

advanced data preprocessing techniques 52

correlation analysis 54-58

data normalization for feature scaling 53

advanced optimization techniques 171

Adam optimization, exploring 175

exploring 171

second-order optimization methods 175, 176

stochastic gradient descent (SGD) 172-174

advanced regularization...

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