Resource link:
Link:/s/127 gbmsiihttvv3wdcx90fg
Password: 08r5 Topic: Python classic example of machine learning
Author: [America] Pratik Josh
Translator: Tao
Douban score: 5.8
Publishing House: People's Posts and Telecommunications Publishing House
Publication year: 20 17-8
Page count: 264
Content introduction:
In today's data-driven world, machine learning is becoming more and more popular. It has been widely used in different fields, such as search engines, robots, driverless cars and so on. This book first introduces the basic knowledge of machine learning through practical cases, and then introduces some slightly more complicated machine learning algorithms, such as support vector machine, extreme random forest, hidden Markov model, conditional random field, deep neural network and so on.
This book is for Python programmers who want to develop applications with machine learning algorithms. It is suitable for beginners to read Python, but being familiar with Python programming methods is of great benefit to experience the sample code.
About the author:
About the author:
Platik Josh
An artificial intelligence expert, focusing on content-based analysis and deep learning, has worked in NVIDIA, Microsoft Research Institute, Qualcomm and several early start-ups in Silicon Valley.
Translator profile:
Tao jiejun
I have been engaged in data analysis for a long time and love Python. I like to communicate face to face with Python every day. I graduated from School of Mechanical and Electrical Engineering of Beijing Jiaotong University with a bachelor's degree and graduated from School of Economics and Management of Beijing Jiaotong University with a master's degree. He worked in China Mobile Design Institute and now works in JD.COM.
Chen Xiaoli
I have been engaged in data analysis for a long time and like Python. I graduated from School of Telecommunications, Beijing Jiaotong University with a bachelor's degree and graduated from this college with a master's degree. At present, he is engaged in scientific and technological literature and patent analysis in Chinese Academy of Sciences.