Book Image

MATLAB for Machine Learning - Second Edition

By : Giuseppe Ciaburro
Book Image

MATLAB for Machine Learning - Second Edition

By: Giuseppe Ciaburro

Overview of this book

Discover why the MATLAB programming environment is highly favored by researchers and math experts for machine learning with this guide which is designed to enhance your proficiency in both machine learning and deep learning using MATLAB, paving the way for advanced applications. By navigating the versatile machine learning tools in the MATLAB environment, you’ll learn how to seamlessly interact with the workspace. You’ll then move on to data cleansing, data mining, and analyzing various types of data in machine learning, and visualize data values on a graph. As you progress, you’ll explore various classification and regression techniques, skillfully applying them with MATLAB functions. This book teaches you the essentials of neural networks, guiding you through data fitting, pattern recognition, and cluster analysis. You’ll also explore feature selection and extraction techniques for performance improvement through dimensionality reduction. Finally, you’ll leverage MATLAB tools for deep learning and managing convolutional neural networks. By the end of the book, you’ll be able to put it all together by applying major machine learning algorithms in real-world scenarios.
Table of Contents (17 chapters)
Free Chapter
1
Part 1: Getting Started with Matlab
4
Part 2: Understanding Machine Learning Algorithms in MATLAB
9
Part 3: Machine Learning in Practice

Implementing a model to predict the stock market

Predicting stock market movements is a complex and challenging endeavor. It involves analyzing various factors and data points to forecast the future direction of stock prices. Fundamental analysts examine a company’s financial health, including its revenue, earnings, debt levels, and growth prospects. They also consider macroeconomic factors such as interest rates, inflation, and government policies that can impact the overall market. Technical analysts study historical price and volume data, looking for patterns and trends in stock charts. They use tools such as moving averages, support and resistance levels, and various technical indicators to make predictions. Identifying current market trends and understanding market cycles can provide insights into potential future movements. Bull markets, bear markets, and sideways markets can affect stock prices differently. Predictions are inherently uncertain, and risk management is...