Tutorial Python 4 in 1

[Impostor Syndrome]

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​

• Length: 556 pages
• Edition: 1
• Language: English
• Publication Date: 2020-07-17
• ISBN-10: B08D7T9J3Z

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


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