Python Programming - (Data Science Mastery) by Andrew Park (Paperback)

Book Synopsis

Python is one of the most beloved programming languages in any circle of programmers. Software engineers, hackers, and Data Scientists alike are in love with the versatility that Python has to offer. Besides, the Object-Oriented feature of Python coupled with its flexibility is also one of the major attractions for this language.

That's the reason why Python is a perfect fit with Data Analysis, Machine Learning and Data Science.

Data is the future. The world of technology as we know it is evolving towards an open-source platform where people share ideas freely. This is seen as the first step towards the decentralization of ideas and eliminating unnecessary monopolies. Therefore, the data, tools, and techniques used in the analysis are easily available for anyone to interpret data sets and get relevant explanations.

The goal of this 4-in-1 bundle is simple: explaining everything you need to know to Master Python. With a special emphasis on the main steps that are needed to correctly implement Data Analysis and Machine Learning algorithms,

• How to install Python
• What are the different Python Data Types and Variables
• Basic Operators of Python Language
• Data Structures and Functions
• Conditional and Loops in Python
• And Much More!

• Object-Oriented Programming (OOP), Inheritance and Polymorphism
• Essential Programming Tools
• Exception Handling
• Working with Files
• And Much More!

• What Data Analysis is all about and why businesses are investing in this sector
• The 5 steps of a Data Analysis
• The 7 Python libraries that make Python one of the best choices for Data Analysis
• Pandas, Jupyter and PyTorch
• And Much More!

• How Data Visualization and Matplotlib can help you to understand the data you are working with.
• Neural Networks
• Decision Trees
• What industries are using data to improve their business with 14 real-world applications
• And So Much More!

Where most books about Python programming are theoretical and have few or little practical examples, this book provides lots of simple, step-by-step examples and illustrations that are used to underline key concepts and help improve your understanding.

Furthermore, topics are carefully selected to give you broad exposure to Python, while not overwhelming you with too much information. Also, the outputs of ALL the examples are provided immediately so you do not have to wait till you have access to your computer to test the examples.

Even if you have never coded before, this is the perfect guide because it breaks down complex concepts into simple steps and in a concise and simple way that fits well with beginners. Regardless of your previous experience, you will learn the steps of Data Analysis, how to implement them, and the most important real-world applications.