Learn all about NumPy

Author:   Innoware Pjp
Publisher:   Independently Published
ISBN:  

9798394954917


Pages:   222
Publication Date:   16 May 2023
Format:   Paperback
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Learn all about NumPy


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Overview

Learn all about NumPy NumPy, short for Numerical Python, is a powerful library in the Python ecosystem that provides support for efficient numerical computations, particularly with large multidimensional arrays and matrices. It serves as a fundamental building block for scientific computing and data analysis in Python. The book covers the following: 1 Introduction to NumPy What is NumPy? History and background Advantages and applications Installing NumPy 2 NumPy Basics NumPy arrays: creation, attributes, and operations Data types and casting Indexing and slicing arrays Array manipulation: reshaping, resizing, and stacking Array broadcasting 3 Array Computations and Mathematical Operations Element-wise operations Mathematical functions and operations Linear algebra with NumPy Random number generation with NumPy 4 Advanced Array Operations Array sorting and searching Fancy indexing and Boolean indexing Array iteration and vectorization Broadcasting rules and examples 5 Working with Structured Data Structured arrays Structured data manipulation Record arrays 6 File Input and Output Reading and writing arrays to files File formats (CSV, text, binary) Memory-mapping files 7 Performance and Optimization Understanding array views and copies Memory management and optimization techniques Vectorization and avoiding loops Profiling and benchmarking NumPy code 8 Integration with Other Libraries Integration with pandas for data analysis Visualization with Matplotlib and NumPy SciPy: advanced scientific computing with NumPy 9 NumPy Best Practices and Tips Writing efficient and readable code Code organization and modularization Debugging and error handling Testing and documenting NumPy code 10 Case Studies and Examples Solving common mathematical problems with NumPy Image processing and manipulation with NumPy Data analysis examples using NumPy 11 Advanced Topics and Future Directions NumPy extensions and alternative libraries GPU acceleration with NumPy Distributed computing with NumPy NumPy in machine learning and deep learning frameworks

Full Product Details

Author:   Innoware Pjp
Publisher:   Independently Published
Imprint:   Independently Published
Dimensions:   Width: 15.20cm , Height: 1.20cm , Length: 22.90cm
Weight:   0.304kg
ISBN:  

9798394954917


Pages:   222
Publication Date:   16 May 2023
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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