Python for Data Science: how to learn basic contents to work with data with this programming language with this beginner’s guide. Machine learning tools, concepts, and data analysis crash course.

Arduino, Matthew

ISBN 13: 9798607163655

Verlag: Independently published, 2020

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Print on Demand. Bestandsnummer des Verkäufers I-9798607163655

Bibliografische Details

Titel: Python for Data Science: how to learn basic ...

Verlag: Independently published

Erscheinungsdatum: 2020

Einband: Softcover

Zustand: New

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How much do you about Python for Data Science?

Python is one of the best languages, suited for programming, especially when it comes to a data scientist.

But, why should you learn this language?

Also, why should you learn this language, if you want to pursue a career in data science?

Python is a very flexible language, besides being powerful and free. It is also an open-source language, besides being simple and coming with easy to read syntax. With the help of python, data manipulation, data visualization, as well as, data analysis becomes very simple. Python also has all the libraries, that are vital for every application of machine learning and scientific processing of data. Though Python is a high-level language, it is also quite easy to learn and is procedure-oriented besides being object-oriented.

Python is widely used also by data scientists because of the presence of a large number of libraries. It can help in performing multiple tasks like web development, database, data mining, image processing, graphical user interface and a lot more. With data science gaining more popularity the programmers need to have deep knowledge in Python, one of the languages required in data science.

That’s why you need a guide like:

“Python for Data Science: how to learn basic contents to work with data with this programming language with this beginner’s guide. Machine learning tools, concepts, and data analysis crash course” by Matthew Arduino

Data Science is all about ETL or extraction-transformation-loading process, which makes Python, very much suited for the purpose. Python has shown a sharp rise, as high as 51%, in its popularity, as a top data science tool. This is because Python can integrate very well with most cloud and platform-as-a-service providers. It also supports multiprocessing, which is helpful for parallel computing. Most importantly, it can be extended with the modules written in other languages like C and C++.

The goal of the eBook is simple: help us understand the importance of Python for data science.

And that’s what you’ll learn:

• Fundamentals of Python for Data Science

• What is Data Science: history of Data Science, data science and artificial intelligence, data science tips and tricks.

• What is Python

• The Python keywords: How to name an identifier, the Python statements, the Comments, bringing in the Python Variables, the Operators, the Python Functions, The Python Classes, Control Flow.

• Python Data Types

• Python Numbers: Python Lists, Python Strings, Python Set, Python dictionary.

Would you like to know more?

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