Mastering Numerical Computing with NumPy: Master scientific computing and perform complex operations with ease

Umit Mert Cakmak, Mert Cuhadaroglu

  • 出版商: Packt Publishing
  • 出版日期: 2018-06-28
  • 售價: $1,610
  • 貴賓價: 9.5$1,530
  • 語言: 英文
  • 頁數: 248
  • 裝訂: Paperback
  • ISBN: 1788993357
  • ISBN-13: 9781788993357
  • 相關分類: Python
  • 海外代購書籍(需單獨結帳)

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商品描述

Enhance the power of NumPy and start boosting your scientific computing capabilities

Key Features

  • 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

Book Description

NumPy is one of the most important scientific computing libraries available for Python. Mastering Numerical Computing with NumPy 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. Once you have got to grips with the basics, you will explore unsupervised learning and clustering algorithms, followed by understanding how to write better NumPy code while keeping advanced considerations in mind. The book also demonstrates the use of different high-performance numerical computing libraries and their relationship with NumPy. You will study how to benchmark the performance of different configurations and choose the best for your system.

By the end of this book, you will have become an expert in handling and performing complex data manipulations.

What you will learn

  • Perform vector and matrix operations using NumPy
  • Perform exploratory data analysis (EDA) on US housing data
  • Develop a predictive model using simple and multiple linear regression
  • Understand unsupervised learning and clustering algorithms with practical use cases
  • Write better NumPy code and implement the algorithms from scratch
  • Perform benchmark tests to choose the best configuration for your system

Who This Book Is For

Mastering Numerical Computing with NumPy is for you if you are a Python programmer, data analyst, data engineer, or a data science enthusiast, who wants to master the intricacies of NumPy and build solutions for your numeric and scientific computational problems. You are expected to have familiarity with mathematics to get the most out of this book.

Table of Contents

  1. Working with NumPy Arrays
  2. Linear Algebra with NumPy
  3. Explanatory Data Analysis of US Housing Data withNumPy Statistics
  4. Predicting Housing Prices Using Linear Regression
  5. Clustering Clients of Wholesale Distributor Using NumPy
  6. Python ML Squad: NumPy, SciPy, Pandas, Scikit-Learn
  7. Advanced Numpy
  8. Overview of High-Performance Numerical Computing Libraries
  9. Performance Benchmarks

商品描述(中文翻譯)

增強 NumPy 的功能,開始提升您的科學計算能力

主要特點
- 掌握數值計算的各個方面,理解 NumPy
- 探索範例以學習探索性數據分析 (EDA)、回歸和聚類
- 訪問 NumPy 函式庫,並使用性能基準測試來選擇合適的工具

書籍描述
NumPy 是 Python 中最重要的科學計算函式庫之一。《掌握數值計算與 NumPy》教您如何達到專家級的能力,以執行複雜的操作,並深入探討高級概念。

從 NumPy 的陣列和函數開始,您將熟悉線性代數概念,以執行向量和矩陣數學運算。您將徹底理解並練習數據處理、探索性數據分析 (EDA) 和預測建模。接著,您將進行實際範例,學習如何使用 NumPy 統計來探索美國住房數據,並使用簡單和多重線性回歸技術開發預測模型。一旦掌握了基礎,您將探索無監督學習和聚類演算法,然後了解如何在考慮高級因素的同時撰寫更好的 NumPy 代碼。本書還展示了不同高性能數值計算函式庫的使用及其與 NumPy 的關係。您將學習如何基準測試不同配置的性能,並選擇最適合您系統的配置。

在本書結束時,您將成為處理和執行複雜數據操作的專家。

您將學到的內容
- 使用 NumPy 執行向量和矩陣運算
- 對美國住房數據進行探索性數據分析 (EDA)
- 使用簡單和多重線性回歸開發預測模型
- 理解無監督學習和聚類演算法及其實際應用案例
- 撰寫更好的 NumPy 代碼並從頭實現演算法
- 執行基準測試以選擇最適合您系統的配置

本書適合誰
《掌握數值計算與 NumPy》適合您,如果您是 Python 程式設計師、數據分析師、數據工程師或數據科學愛好者,想要掌握 NumPy 的細節並為您的數值和科學計算問題構建解決方案。您應該對數學有一定的熟悉度,以便充分利用本書。

目錄
1. 使用 NumPy 陣列
2. NumPy 的線性代數
3. 使用 NumPy 統計對美國住房數據進行解釋性數據分析
4. 使用線性回歸預測住房價格
5. 使用 NumPy 對批發分銷商的客戶進行聚類
6. Python ML 團隊:NumPy、SciPy、Pandas、Scikit-Learn
7. 高級 NumPy
8. 高性能數值計算函式庫概述
9. 性能基準測試