PYTHON: Learn Coding Programs with Python Programming and Master Data Analysis & Analytics

English | 2020 | ASIN: B08D7T9J3Z | 109 Pages | PDF, EPUB, AZW3 | 30.2 MB

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…

_https://mega.nz/file/Bx1D3LDK#BgDbTJNXDvxotW6QMrQfT1A-_refEXMMYjGHS8l-Mss

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