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Book SynopsisIf you want to learn Python in one week (or less) and learn it well, with useful applications to Data Analysis, Machine Learning and Data Science, then keep reading.
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,
In manuscript one, Python for Beginners, you will learn:
In manuscript two, Python Advanced Guide, you will master:
In manuscript three, Python for Data Analysis, you will learn:
In manuscript four, Applications to Data Science, you will understand:
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.
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