Processing ......
FreeComputerBooks.com
Links to Free Computer, Mathematics, Technical Books all over the World
 
From Python to NumPy
🌠 Top Free Unix/Linux Books - 100% Free or Open Source!
  • Title: From Python to NumPy
  • Author(s) Nicolas P. Rougier
  • Publisher: LaBRI (May 2017); eBook (Creative Commons Licensed)
  • License(s): CC BY-NC-SA 4.0
  • Hardcover/Paperback: N/A
  • eBook: HTML
  • Language: English
  • ISBN-10: N/A
  • ISBN-13: N/A
  • Share This:  

Book Description

NumPy is one of the most important scientific computing libraries available for Python. This book teaches you how to achieve expert level competency to perform complex operations, with in-depth coverage of advanced concepts.

Beginning with NumPy's arrays and functions, you will familiarize yourself with linear algebra concepts to perform vector and matrix math operations. You will thoroughly understand and practice data processing, exploratory data analysis (EDA), and predictive modeling.

You will then move on to working on practical examples which will teach you how to use NumPy statistics in order to explore US housing data and develop a predictive model using simple and multiple linear regression techniques.

  • Grasp all aspects of numerical computing and understand NumPy
  • Explore examples to learn exploratory data analysis (EDA), regression, and clustering
  • Access NumPy libraries and use performance benchmarking to select the right tool
About the Authors
  • N/A
Reviews, Ratings, and Recommendations: Related Book Categories: Read and Download Links: Similar Books:
  • Mathematical Python (Patrick Walls)

    This book is an introduction to mathematical computing including basic Python programming, scientific computing with NumPy, SciPy and Matplotlib, applications in calculus, linear algebra and differential equations.

  • Guide to NumPy (Travis E. Oliphant)

    This book is for programmers, scientists, or engineers, who have basic Python knowledge and would like to be able to do numerical computations with Python. It will give you a solid foundation in NumPy arrays and universal functions.

  • NumPy Tutorials (Usman Malik, Anne Bonner, et al)

    They provide everything you need to know to get started with NumPy. They also explain the basics of NumPy such as its architecture and environment, discusses the various array functions, types of indexing, etc. With examples for better understanding.

  • Programming for Computations - Python 3 Edition

    This book outlines the shortest possible path from no previous experience with programming to a set of skills that allows students to write simple programs for solving common mathematical problems with numerical methods in the context.

  • Scipy Lecture Notes (Emmanuelle Gouillart, et al)

    This book teaches the scientific Python ecosystem, a quick introduction to central tools and techniques. It is for programmers from beginner to expert. Work on real-world problems with SciPy, NumPy, Pandas, scikit-image, and other Python libraries.

  • SciPy Programming Succinctly (James McCaffrey)

    This book offers readers a quick, thorough grounding in knowledge of the Python open source extension SciPy. The SciPy library, accompanied by its interdependent NumPy, offers Python programmers advanced functions that work with arrays and matrices.

  • Computational Physics with Python (Eric Ayars)

    This book provides an unusually broad survey of the topics of modern computational physics. Its philosophy is rooted in learning by doing, with new scientific materials as well as with the Python programming language.

  • Solving PDEs in Python: The FEniCS Tutorial I (H. Langtangen)

    This book offers a concise and gentle introduction to finite element programming in Python based on the popular FEniCS software library. Using a series of examples, it guides readers through the essential steps to quickly solving a PDE in FEniCS.

  • Python Scripting for Computational Science (Hans Langtangen)

    This brilliantly useful book shows computational scientists how to develop tailored, flexible, and human-efficient working environments built from small scripts written in the easy-to-learn, high-level Python language.

Book Categories
:
Other Categories
Resources and Links