Data Science from Scratch 2024 pdf epub mobi 电子书

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Data Science from Scratch 2024 pdf epub mobi 电子书著者简介

Joel Grus is a research engineer at the Allen Institute for Artificial Intelligence. Previously he worked as a software engineer at Google and a data scientist at several startups. He lives in Seattle, where he regularly attends data science happy hours. He blogs infrequently at joelgrus.com and tweets all day long at @joelgrus.

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发表于2024-09-12

Data Science from Scratch 2024 pdf epub mobi 电子书

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Data Science from Scratch 电子书读后感

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数据科学是一个蓬勃发展、前途无限的行业，有人将数据科学家称为“21世纪头号性感职业”。本书从零开始讲解数据科学工作，教授数据科学工作所必需的黑客技能，并带领读者熟悉数据科学的核心知识——数学和统计学。作者选择了功能强大、简单易学的Python语言环境，亲手搭建工具...

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这本书可以作为 Data Science 101 ，只是一本基于 Python 学习 Data Science 的指南，我觉得里面最有价值的就是 For Further Exploration 部分了。

评分☆☆☆☆☆

这本书可以作为 Data Science 101 ，只是一本基于 Python 学习 Data Science 的指南，我觉得里面最有价值的就是 For Further Exploration 部分了。

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出版者:O'Reilly Media

作者:Joel Grus

出品人:

页数:406

译者:

出版时间:2019-5-13

价格:USD 59.99

装帧:Paperback

isbn号码:9781492041139

丛书系列:

图书标签: Python 大数据 Science" "Data py DM

Data Science from Scratch 2024 pdf epub mobi 电子书图书描述

To really learn data science, you should not only master the tools—data science libraries, frameworks, modules, and toolkits—but also understand the ideas and principles underlying them. Updated for Python 3.6, this second edition of Data Science from Scratch shows you how these tools and algorithms work by implementing them from scratch.

If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with the hacking skills you need to get started as a data scientist. Packed with new material on deep learning, statistics, and natural language processing, this updated book shows you how to find the gems in today’s messy glut of data.

Get a crash course in Python

Learn the basics of linear algebra, statistics, and probability—and how and when they’re used in data science

Collect, explore, clean, munge, and manipulate data

Dive into the fundamentals of machine learning

Implement models such as k-nearest neighbors, Naïve Bayes, linear and logistic regression, decision trees, neural networks, and clustering

Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

Data Science from Scratch 2024 pdf epub mobi 电子书

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