没有合适的资源？快使用搜索试试~ 我知道了~

首页用Numpy、Scipy、pandas、Scikit-Learn、XGBoost、Tensorflow、Keras入门数据科学

用Numpy、Scipy、pandas、Scikit-Learn、XGBoost、Tensorflow、Keras入门数据科学

数据科学

入门学习

XGB

keras

Python

需积分: 40 403 浏览量更新于2023-05-26 评论收藏 650KB PDF 举报

身份认证购VIP最低享 7 折!

领优惠券(最高得80元）

试读

18页

用Numpy、Scipy、pandas、Scikit-Learn、XGBoost、Tensorflow、Keras入门数据科学,Data Science with Python explained.

资源详情

资源评论

资源推荐

Data Science with Python explained

An overview of using Python for data science

including Numpy, Scipy, pandas, Scikit‑

Learn, XGBoost, TensorFlow andKeras.

So you’ve heard of data science and you’ve heard of Python.

You want to explore both but have no idea where to start — data

science is pretty complicated, after all.

Don’t worry — Python is one of the easiest programming languages to

learn. And thanks to the hard work of thousands of open source

contributors, you can do data science, too.

If you look at the contents of this article, you may think there’s a lot

to master, but this article has been designed to gently increase the

difficulty as we go along.

One article obviously can’t teach you everything you need to know

about data science with python, but once you’ve followed along you’ll

know exactly where to look to take the next steps in your data science

journey.

Contents:

Why Python?

Installing Python

Using Python for Data Science

Numeric computation in Python

Statistical analysis in Python

Data manipulation in Python

Working with databases in Python

Carl Dawson

Mar 24

13 min read

•

Data engineering in Python

Big data engineering in Python

Further statistics in Python

Machine learning in Python

Deep learning in Python

Data science APIs in Python

Applications in Python

Summary

Why Python?

Python, as a language, has a lot of features that make it an excellent

choice for data science projects.

It’s easy to learn, simple to install (in fact, if you use a Mac you

probably already have it installed), and it has a lot of extensions that

make it great for doing data science.

•

Just because Python is easy to learn doesn’t mean its a toy

programming language — huge companies like Google use Python for

their data science projects, too. They even contribute packages back

to the community, so you can use the same tools in your projects!

You can use Python to do way more than just data science — you can

write helpful scripts, build APIs, build websites, and much much

more. Learning it for data science means you can easily pick up all

these other things as well.

Things tonote

There are a few important things to note about Python.

Right now, there are two versions of Python that are in common use.

They are versions 2 and 3.

Most tutorials, and the rest of this article, will assume that you’re

using the latest version of Python 3. It’s just good to be aware that

sometimes you can come across books or articles that use Python 2.

The difference between the versions isn’t huge, but sometimes

copying and pasting version 2 code when you’re running version 3

won’t work — you’ll have to do some light editing.

The second important thing to note is that Python really cares about

whitespace (that’s spaces and return characters). If you put

whitespace in the wrong place, your programme will very likely throw

an error.

There are tools out there to help you avoid doing this, but with

practice you’ll get the hang of it.

If you’ve come from programming in other languages, Python might

feel like a bit of a relief: there’s no need to manage memory and the

community is very supportive.

If Python is your first programming language you’ve made an

excellent choice. I really hope you enjoy your time using it to build

awesome things.

Installing Python

The best way to install Python for data science is to use the Anaconda

distribution (you’ll notice a fair amount of snake-related words in the

community).

It has everything you need to get started using Python for data

science including a lot of the packages that we’ll be covering in the

article.

If you click on Products -> Distribution and scroll down, you’ll see

installers available for Mac, Windows and Linux.

Even if you have Python available on your Mac already, you should

consider installing the Anaconda distribution as it makes installing

other packages easier.

If you prefer to do things yourself, you can go to the official Python

website and download an installer there.

Package Managers

Packages are pieces of Python code that aren’t a part of the language

but are really helpful for doing certain tasks. We’ll be talking a lot

about packages throughout this article so it’s important that we’re set

up to use them.

Because the packages are just pieces of Python code, we could copy

and paste the code and put it somewhere the Python interpreter (the

thing that runs your code) can find it.

剩余17页未读，继续阅读

OC-暂停-取消-继续NSBlockOperation

基于51单片机的AD转换设计

基于https://blog.csdn.net/Is_Superman/article/details/108421606文章的源码和proteus图

android studio 学生信息管理系统实现源码（安卓开发教程课后练习）

android studio 学生信息管理系统实现源码（安卓开发教程课后练习）android studio 学生信息管理系统实现源码（安卓开发教程课后练习）android studio 学生信息管理系统实现源码（安卓开发教程课后练习）android studio 学生信息管理系统实现源码（安卓开发教程课后练习）android studio 学生信息管理系统实现源码（安卓开发教程课后练习）andro

2022-2023第2学期+专升本+计算机图形学+第2次平时作业

windows 用户权限管理工具，NSudoLG-用户权限提升工具

dsp_lite_5.5.0_230511_1.apk

毕业设计-基于微信小程序的校园圈子小程序（包括源码，数据库，教程）.zip

小程序毕业设计，小程序课程设计，含有代码注释，新手也可看懂。毕业设计、期末大作业、课程设计、高分必看，下载下来，简单部署，就可以使用。包含：项目源码、数据库脚本、软件工具等，该项目可以作为毕设、课程设计使用，前后端代码都在里面。该系统功能完善、界面美观、操作简单、功能齐全、管理便捷，具有很高的实际应用价值。项目都经过严格调试，确保可以运行！可以放心下载 1. 技术组成前端：小程序

ESP ST7701驱动代码

MC33272 友顺UTC 电子元器件芯片.pdf

MC33272 友顺UTC 电子元器件芯片

tox33

粉丝: 64
资源: 306

上传资源快速赚钱

我的内容管理收起

我的资源快来上传第一个资源

我的收益

登录查看自己的收益

我的积分登录查看自己的积分

我的C币登录后查看C币余额

我的收藏

我的下载

下载帮助

会员权益专享

用Numpy、Scipy、pandas、Scikit-Learn、XGBoost、Tensorflow、Keras入门数据科学

评论0

会员权益专享

最新资源

用Numpy、Scipy、pandas、Scikit-Learn、XGBoost、Tensorflow、Keras入门数据科学

评论0

python machine learning

python-programmers-artificial-intelligence-studies

请问python如果做人工智能开发需要添加那些库

在什么软件使用python

简述什么是anconda

python3.8机器学习库版本对应

python本地whl库大全

Python都有哪些高级库

列出python已安装的包

新词挖掘 python

适合小白写的项目 烘焙坊前端项目源码

OC-暂停-取消-继续NSBlockOperation

基于51单片机的AD转换设计

android studio 学生信息管理系统实现源码（安卓开发教程课后练习）

2022-2023第2学期+专升本+计算机图形学+第2次平时作业

windows 用户权限管理工具，NSudoLG-用户权限提升工具

dsp_lite_5.5.0_230511_1.apk

毕业设计-基于微信小程序的校园圈子小程序（包括源码，数据库，教程）.zip

ESP ST7701驱动代码

MC33272 友顺UTC 电子元器件芯片.pdf

会员权益专享

最新资源

适合小白写的项目烘焙坊前端项目源码