Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib Second Edition
Robert Johansson
- 出版商: Apress
- 出版日期: 2018-12-25
- 定價: $2,450
- 售價: 6.0 折 $1,470
- 語言: 英文
- 頁數: 700
- 裝訂: Paperback
- ISBN: 1484242459
- ISBN-13: 9781484242452
-
相關分類:
Python、程式語言、Data Science
-
相關翻譯:
Python 科學計算和數據科學應用 : 使用 NumPy、SciPy 和 matplo, 2/e (簡中版)
-
其他版本:
Numerical Python: Scientific Computing and Data Science Applications with Numpy, Scipy and Matplotlib Third Edition
買這商品的人也買了...
-
$301Xilinx Zynq SoC 與嵌入式 Linux 設計實戰指南 (兼容ARM Cortex-A9的設計方法) -
$1,848Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists -
Python 資料科學學習手冊 (Python Data Science Handbook: Essential Tools for Working with Data)$780$616 -
實戰機器學習｜以深度學習演算企業資料$450$383 -
Math Adventures with Python: An Illustrated Guide to Exploring Math with Code (Paperback)$1,050$998 -
2019．2020 系統重灌、調校、故障排除與資料搶救自己來 (超值附贈314分鐘影音講解)$450$356 -
TensorFlow 與 Keras - Python 深度學習應用實務$650$553 -
機器學習的數學基礎 : AI、深度學習打底必讀$580$458 -
深度學習的數學地圖 -- 用 Python 實作神經網路的數學模型 (附數學快查學習地圖)$580$458 -
決心打底！Python 深度學習基礎養成$690$587 -
AI 醫療 DEEP MEDICINE (Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again)$680$537 -
AI for Immunology$1,370$1,302 -
速查! 數學大百科事典 – 127 個公式、定理、 法則$500$395 -
Scientific Computing with Python - Second Edition: High-performance scientific computing with NumPy, SciPy, and pandas$1,810$1,720 -
Biology: A Global Approach, 12/e (Paperback)$2,100$2,058 -
打下最紮實 AI 基礎不依賴套件：手刻機器學習神經網路穩健前進$1,200$948 -
FPGA 時序約束與分析$414$393 -
Python 論文數據統計分析$540$486 -
Python 程式設計 ─ AI 與資料科學應用, 2/e$540$529 -
$352Xilinx FPGA 開發實用教程, 2/e -
人手一本的資安健診實作課：不是專家也能自己動手做！（Win10 / Win11適用）$560$437 -
資料科學基礎數學 (Essential Math for Data Science)$680$537 -
FPGA 開發實用教程 — 基於 Xilinx 和 Verilog HDL (微課版)$294$279 -
未來數位科技活用大全：從 AI 協作、程式設計、資訊安全到大數據分析$580$452 -
Biology Made Easy$830$789
相關主題
商品描述
Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute solutions and mathematically model applications in big data, cloud computing, financial engineering, business management and more.
Numerical Python, Second Edition, presents many brand-new case study examples of applications in data science and statistics using Python, along with extensions to many previous examples. Each of these demonstrates the power of Python for rapid development and exploratory computing due to its simple and high-level syntax and multiple options for data analysis.
After reading this book, readers will be familiar with many computing techniques including array-based and symbolic computing, visualization and numerical file I/O, equation solving, optimization, interpolation and integration, and domain-specific computational problems, such as differential equation solving, data analysis, statistical modeling and machine learning.
What You'll Learn
- Work with vectors and matrices using NumPy
- Plot and visualize data with Matplotlib
- Perform data analysis tasks with Pandas and SciPy
- Review statistical modeling and machine learning with statsmodels and scikit-learn
- Optimize Python code using Numba and Cython
商品描述(中文翻譯)
利用Python及其標準庫中的數值和數學模塊，以及流行的開源數值Python包（如NumPy、SciPy、FiPy、matplotlib等），本完全修訂的第二版更新了每個包的最新細節和Jupyter項目的更改，演示了如何在大數據、雲計算、金融工程、商業管理等領域中數值計算解決方案和數學建模應用。
《數值Python，第二版》提供了許多全新的數據科學和統計學應用案例，展示了使用Python進行快速開發和探索性計算的強大功能，這得益於其簡單高效的語法和多種數據分析選項。
閱讀本書後，讀者將熟悉許多計算技術，包括基於數組和符號的計算、可視化和數值文件I/O、方程求解、優化、插值和積分，以及特定領域的計算問題，如微分方程求解、數據分析、統計建模和機器學習。
你將學到什麼：
- 使用NumPy處理向量和矩陣
- 使用Matplotlib繪製和可視化數據
- 使用Pandas和SciPy執行數據分析任務
- 使用statsmodels和scikit-learn進行統計建模和機器學習
- 使用Numba和Cython優化Python代碼
本書適合對如何使用Python及其相關生態系統進行數值計算感興趣的開發人員。
