Python Fast Track

Python Fast Track

  • Sanjiban Sekhar Roy
  • Arnav Chouhan
  • Naman Khera
Publisher:ElsevierISBN 13: 9780443338243ISBN 10: 0443338248

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Know about the book -

Python Fast Track is written by Sanjiban Sekhar Roy and published by Elsevier. It's available with International Standard Book Number or ISBN identification 0443338248 (ISBN 10) and 9780443338243 (ISBN 13).

Python Fast Track: A Complete Guide to Rapidly Mastering and Applying Python Programming adopts a simplified writing style and provides clear explanations to ensure ease of understanding, making it an ideal resource for those new to Python. Starting with the basics, the book covers fundamental concepts such as variables, data types, printing and prompting, lists, dictionaries, tuples, control structure, functions, and object-oriented concepts. The book includes everything you need to understand and apply more advanced programming techniques such as file handling, exception handling, and regex.This great resource is created especially for those who want to apply Python for their research and professional work in scientific computing, data analysis and machine learning, including chapters on NumPy and Pandas, two of the most popular Python application libraries. It demonstrates how to effectively master key applications of Python such as web development, software creation, task automation, and data analysis. The book covers data analysis and machine learning tasks that greatly benefit from Python, thanks to libraries such as TensorFlow and Keras that enable efficient coding. - Explains the core concepts of Python programming in a simplified way that is suitable for people who have little or no programming experience - Incorporates a wide range of simple, step-by-step examples and illustrations to highlight fundamental concepts so readers can learn easily - Provides practice exercises designed to expedite the learning process and provide hands-on application experience - Offers a wide range of functionality, from basic processes to complex operations, including chapters on Pandas and NumPy, two of the most popular Python libraries for data analysis