Machine learning system design. Python PDF

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Today, machine learning is making a boom on the internet, and Python is a great language for developing machine learning systems. As a dynamic language, it supports rapid exploration and experimentation, and the number of machine learning algorithm libraries for Python is increasing. The most important feature of this book is to combine examples to teach readers how to solve practical problems through machine learning.
This book will show readers how to discover patterns from raw data, start with the relationship between Python and machine learning, introduce some libraries, and then start comparing formal project development based on datasets, involving modeling, recommendations and improvements, and sound and image processing. With the popular open source Library, we can learn how to process text, pictures, and sounds efficiently. At the same time, readers can also learn how to evaluate, compare and select the applicable machine learning techniques.
For a few examples, we'll show you how to classify StackOverflow's answers by quality, how to know if a music file is jazz, or heavy metal rock style. In addition, the book covers topics such as modeling, shopping habits analysis, and advanced content such as cloud computing. In short, through the study of this book, the reader can grasp the construction of their own system of all aspects of knowledge, and apply it to solve their own practical problems.
As long as the reader has a certain Python programming experience, to install and use the Open Source Library, it is enough, even if there is no understanding of machine learning does not matter. This book does not talk about the math behind machine learning algorithms.

Author Profile:
Willi Richert
PhD in machine learning and robotics, currently serving on the Microsoft Bing Search core research and development team. He has worked on a variety of machine learning areas, including active learning and statistical machine translation.
Luis Pedro Coelho
Computational biologists, mainly concerned with the processing of bio-image informatics and large-scale image data, are committed to the application of machine learning techniques in the image analysis of biological specimens, and are the main developers of the Python Computer Vision Library Mahotas. He started developing open source software in 1998, began Python development in 2004, and contributed code to multiple Python open source libraries. In addition, Luis has a PhD from the world's leading Carnegie Mellon University in Machine learning and has published numerous scientific papers.
Translator Profile:
Liu Feng
Senior Research Engineer of Baidu lbs Map Foundation Business Department, PhD, Department of Computer Engineering, Nanyang Technological University, Singapore, including machine learning, fuzzy neural networks, etc. 2010 joined Baidu, mainly engaged in big data analysis and mining work, in recent years focused on wireless positioning, user trajectory and other lbs big Data mining and machine learning applications.
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Machine learning system design. Python PDF