PYTHON: Learn Coding Programs with Python Programming and Master Data Analysis & Analytics, Data Science and Machine Learning with the Complete Python for Beginners Crash Course – 4 Books in 1

Book Description

Do you want to learn Python Programming well and fast?
Are you looking for the best Python for Data Analysis and Analytics course?
Do you want to learn Data Science and how to leverage Python for it?
Do want to learn Python Machine Learning and start implementing models?

If yes, then this Python for Beginners Crash Course is for you. This is the most complete Python guide with 4 Manuscripts in 1 book:
1-Python Programming
2-Python for Data Analysis & Analytics
3-Python for Data Science
4-Python Machine Learning

A great opportunity: Simplicity, Best Order and Selection of topics to Learn Fast and Selected Practice Exercises and Examples.

In Manuscript 1 “Python Programming” you’ll learn:
– What is Python
– How to install Python and what is the best distribution
– What are data types and variables
– How to work with numbers in Python
– What operators there are in Python and when to use them
– How to manipulate Strings
– How to implement Program Flow Controls
– How to implement loops in Python
– What are Python lists, Tuples, Sets and Fictionaries and how to use them
– How to create modules and functions
– How to program according to the Object Oriented paradigm
– How to create classes
– What are and how to use Inheritance, Polymorphism, Abstraction and Encapsulation
And much more…

In Manuscript 2 “Python for Data Analysis & Analytics” you’ll learn:
– What Data Analysis is and why it is important
– What are the different types of Data Analysis
– What are the 6 key steps of the Data Analysis process that you should follow
– What are the applications of Data Analysis and Analytics
– How to set up the Python environment for Data Analysis
– What are and how to use Python Data Structures
– How to work with IPython/Jupyter Notebook
– How to work with NumPy
– How to visualize data with Matplotlib
– What other visualization libraries are out there
– Why is Big Data important and how to get the best out of it
– How to leverage Neural Networks for Data Analysis
And much more…

In Manuscript 3 “Python for Data Science” you’ll learn:
– What is Data Science and what does it encompass
– What are the 5 key steps of the Data Science process that you should follow
– How to set up the Python environment for Data Science
– How to work with Seaborn data visualization module
– How run scientific analysis with SciPy
– How to do Data Mining
– What are the most important Machine Learning Algorithms
– How to leverage the Scikit-Learn module for Machine Learning
– How to leverage Data Science in the Cloud
– What are the most important application of Data Science
And much more…

In Manuscript 4 “Python Machine Learning” you’ll learn
– What is Machine Learning and what does it encompass
– What are the 7 Steps of the Machine Learning Process
– What are the different Machine Learning types
– How is Machine Learning applied to the real world
– What are the main Data Mining techniques
– How to do Data Mining
– How to best set up the Python environment for Machine Learning
– What are the most important Python libraries for Machine Learning
– How to leverage Tensorflow for Deep Learning
– How to work with Keras for Deep Learning
– How to leverage PyTorch for Recurrent Neural Networks
And much more…

Click the BUY button and download the book now to start learning well and fast!

中文：

书名：PYTHON: Learn Coding Programs with Python Programming and Master Data Analysis & Analytics, Data Science and Machine Learning with the Complete Python for Beginners Crash Course – 4 Books in 1

您想要又好又快地学习Python编程吗？
您是否正在寻找最适合数据分析和分析的Python课程？
您是否想学习数据科学，以及如何利用Python来学习数据科学？
想要学习Python机器学习并开始实现模型吗？

如果是，那么这个面向初学者的速成课程就是为你准备的。这是最完整的一本书中包含4个手稿的Python指南：
1-Python Programming
2-用于数据分析和分析的Python
3-面向数据科学的Python
4-Python机器学习

A great opportunity：简单性、最佳顺序和选题以快速学习和精选练习和范例。

In Manuscript 1 “Python Programming“你会学到：
&#8211；什么是Python
&#8211；如何安装Python？最佳发行版是什么？
&#8211；什么是数据类型和变量
&#8211；如何在Python中使用数字
&#8211；Python中有哪些运算符以及何时使用它们
– How to manipulate Strings
&#8211；如何实现程序流控制
&#8211；如何在Python中实现循环
&#8211；什么是Python列表、元组、集合和虚构函数以及如何使用它们
– How to create modules and functions
&#8211；如何根据面向对象范例编程
&#8211；如何创建类
什么是以及如何使用继承、多态、抽象和封装
还有更多&#8230；

In Manuscript 2 “用于数据分析和分析的Python“你会学到：
&#8211；什么是数据分析以及它为什么重要
&#8211；数据分析的不同类型有哪些
数据分析流程中您应该遵循的6个关键步骤是什么
– What are the applications of Data Analysis and Analytics
&#8211；如何设置用于数据分析的Python环境
&#8211；什么是以及如何使用Python数据结构
– How to work with IPython/Jupyter Notebook
– How to work with NumPy
&#8211；如何使用Matplotlib可视化数据
&#8211；还有哪些可视化程序库
&#8211；为什么大数据很重要，以及如何充分利用大数据
&#8211；如何利用神经网络进行数据分析
And much more…

In Manuscript 3 “Python for Data Science“你会学到：
什么是数据科学？它包括什么？
数据科学流程中您应该遵循的5个关键步骤是什么
– How to set up the Python environment for Data Science
&#8211；如何使用海运数据可视化模块
&#8211；如何使用SciPy进行科学分析
&#8211；如何进行数据挖掘
最重要的机器学习算法是什么？
&#8211；如何利用Scikit-学习模块进行机器学习
&#8211；如何在云中利用数据科学
数据科学最重要的应用是什么
And much more…

In Manuscript 4 “巨蟒机器学习” you’ll learn
什么是机器学习？它包括什么？
机器学习过程的7个步骤是什么
&#8211；有哪些不同的机器学习类型
&#8211；机器学习如何应用于现实世界
主要的数据挖掘技术有哪些
&#8211；如何进行数据挖掘
&#8211；如何最好地为机器学习设置Python环境
&#8211；机器学习最重要的Python库是什么
&#8211；如何利用TensorFlow进行深度学习
&#8211；如何使用Kera进行深度学习
&#8211；如何将PyTorch用于递归神经网络
And much more…

点击购买按钮，现在就下载这本书，开始快速学习！