想真正学会数据科学，你不仅要掌握工具——数据科学库、框架、模块和工具包——还要理解它们背后的思想和原理。更新的《数据科学入门》第2版为你展示了这些工具和算法是如何从零开始实现的。
如果你具备数学能力和一些编程技能，作者Joel Grus将会帮你熟悉数据科学相关的核心数学和统计学知识，以及作为一名数据科学家所需的黑客技巧。这本更新的书还包含了关于深度学习、统计学和自然语言处理的新资料，为你展示了如何在日常繁杂冗余的数据中找到宝石。

Preface to the Second Edition
Preface to the First Edition
1.Introduction
The Ascendance of Data
What Is Data Science?
Motivating Hypothetical： DataSciencester
Finding Key Connectors
Data Scientists You May Know
Salaries and Experience
Paid Accounts
Topics of Interest
Onward
2.A Crash Course in Python
The Zen of Python
Getting Python
Virtual Environments
Whitespace Formatting
Modules
Functions
Strings
Exceptions
Lists
Tuples
Dictionaries
defauhdict
Counters
Sets
Control Flow
Truthiness
Sorting
List Comprehensions
Automated Testing and assert
Object-Oriented Programming
Iterables and Generators
Randomness
Regular Expressions
Functional Programming
zip and Argument Unpacking
args and kwargs
Type Annotations
How to Write Type Annotations
Welcome to DataSciencester！
For Further Exploration
3.Visualizing Data
matploflib
Bar Charts
Line Charts
Scatterplots
For Further Exploration
4.Linear Algebra
……