دانلود کتاب دستور العمل های یادگیری ماشین متلب

Machine Learning is becoming important in every engineering discipline. For example:
1. Autonomous cars: Machine learning is used in almost every aspect of car control systems. 2. Plasma physicists use machine learning to help guide experiments on fusion reactors. TAE Technologies has used it with great success in guiding fusion experiments. The Princeton Plasma Physics Laboratory (PPPL) 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.
While many excellent packages are available from commercial sources and open source repositories, it is valuable to understand how these algorithms work. Writing your own al-gorithms is valuable both because it gives you insight into the commercial and open source packages and also because it gives you the background to write your custom Machine Learning software specialized for your application.
MATLAB had its origins for that very reason. Scientists who needed to do operations on matrices used numerical software written in FORTRAN. At the time, using computer lan-guages required the user to go through the write-compile-link-execute process which was time-consuming and error-prone. MATLAB presented the user with a scripting language that allowed the user to solve many problems with a few lines of a script that executed instantaneously. MAT-LAB has built-in visualization tools that helped the user better understand the results. Writing MATLAB was a lot more productive and fun than writing FORTRAN.
The goal of MATLAB Machine Learning Recipes: A Problem-Solution Approach is to help all users 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 MATLAB, can help them solve problems in their areas of expertise.