Machine learning is becoming important in every engineering discipline. For example:
1. Autonomouscars.Machinelearningisusedinalmosteveryaspectofcarcontrolsystems.
2. Plasma physicists use machine learning to help guide experiments on fusion reactors. TAE Systems has used it with great success in guiding fusion experiments. The Princeton Plasma Physics Laboratory has used it for the National Spherical Torus Experiment to study a promising candidate for a nuclear fusion power plant.
3. It is used in finance for predicting the stock market.
4. Medical professionals use it for diagnoses.
5. Law enforcement, and others, use it for facial recognition. Several crimes have been solved using facial recognition!
6. An expert system was used on NASA’s Deep Space 1 spacecraft.
7. Adaptive control systems steer oil tankers.
There are many, many other examples.
The goal of MATLAB Machine Learning Recipes: A Problem–Solution Approach is to help all users to harness the power of MATLAB to solve a wide range of learning problems. The book has something for everyone interested in machine learning. It also has material that will allow people with an interest in other technology areas to see how machine learning, and MAT- LAB, can help them to solve problems in their areas of expertise.
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