Название: A Concise Introduction to Machine Learning Автор: A.C. Faul Издательство: Chapman and Hall/CRC Год: 2019 Страниц: 335 Язык: английский Формат: pdf (true) Размер: 21.1 MB
Machine Learning is known under many names such as Machine Learning, Artificial Intelligence, Pattern Recognition, Data Mining, Data Assimilation, and Big Data, to list but a few. It developed in many areas of science, such as in physics, engineering, computer science, and mathematics in parallel and independently. For example it is used for Spam Filtering, Optical Character Recognition (OCR), Search Engines, Computer Vision, Natural Language Processing (NLP), Advertising, Fraud Detection, Robotics, Data Prediction, Material Discovery, Astronomy. This makes it sometimes difficult to find a solution for a particular problem in the literature, simply because different words and phrases are used for the same concept.
This book aims to alleviate this. A common concept, but known in several disciplines under different names, is described using mathematics as the common language. Readers will find the index useful to find a particular topic as it is known to them. The index is comprehensive, making it easy to find the required information. Hopefully, the book will prove useful as a reference and make it an essential on the bookshelves of anybody employing Machine Learning techniques.
The emphasis of the book is on the question of Why – only if why an algorithm is successful is understood, can it be properly applied, and the results trusted. Algorithms are often taught side by side without showing the similarities and differences between them. This book addresses the commonalities, and aims to give a thorough and in-depth treatment and develop intuition, while remaining concise.
Techniques are illustrated by MATLAB implementations. The main purpose is to show the inner workings of the method in order to develop an intuition.
This useful reference should be an essential on the bookshelves of anyone employing Machine Learning techniques.
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A Concise Introduction to Machine Learning 
