Machine Learning for Absolute Beginners 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

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Oliver Theobald 作者

译者

出版日期

131 页数

USD 10.99 价格

Paperback

丛书系列

9781520951409 图书编码

Machine Learning for Absolute Beginners 在线电子书图书标签: 机器学习计算机理工

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发表于2024-11-26

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Machine Learning for Absolute Beginners 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Machine Learning for Absolute Beginners 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

Machine Learning for Absolute Beginners 在线电子书用户评价

评分☆☆☆☆☆

说的还是很清楚的，不涉及具体算法推导，简单介绍机器学习的分类算法，基本过程，最后一个实例作为总结不错

评分☆☆☆☆☆

最浅显易懂的机器学习入门书了

评分☆☆☆☆☆

说的还是很清楚的，不涉及具体算法推导，简单介绍机器学习的分类算法，基本过程，最后一个实例作为总结不错

评分☆☆☆☆☆

说的还是很清楚的，不涉及具体算法推导，简单介绍机器学习的分类算法，基本过程，最后一个实例作为总结不错

评分☆☆☆☆☆

说的还是很清楚的，不涉及具体算法推导，简单介绍机器学习的分类算法，基本过程，最后一个实例作为总结不错

Machine Learning for Absolute Beginners 在线电子书著者简介

Machine Learning for Absolute Beginners 在线电子书图书目录

Machine Learning for Absolute Beginners 在线电子书 pdf 下载 txt下载 epub 下载 mobi 在线电子书下载

Machine Learning for Absolute Beginners 在线电子书图书描述

The manner in which computers are now able to mimic human thinking to process information is rapidly exceeding human capabilities in everything from chess to picking the winner of a song contest.

In the modern age of machine learning, computers do not strictly need to receive an ‘input command’ to perform a task, but rather ‘input data’. From the input of data they are able to form their own decisions and take actions virtually as a human would. But given it is a machine, it can consider many more scenarios and execute far more complicated calculations to solve complex problems.

This is the element that excites data scientists and machine learning engineers the most. The ability to solve complex problems never before attempted.

This is also perhaps one reason why you are looking at purchasing this book, to gain a beginner's introduction to machine learning. This book provides a plain English introduction to the following topics: - Artificial Intelligence - Big Data - Downloading Free Data Sets - Regression - Support Vector Machine Algorithms - Deep Learning/Neural Networks - Data Reduction - Clustering - Association Analysis - Machine Learning Careers

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