 Название: Mastering NumPy: The Ultimate Guide to Data Manipulation in Python
Автор: Muslum Yildiz
Издательство: Independently published
Год: October 21, 2024
Страниц: 280
Язык: английский
Формат: epub
Размер: 40.6 MB
Step into the future of data science and artificial intelligence with "Mastering NumPy: The Ultimate Guide to Data Manipulation in Python". This book is not just another technical guide; it’s your gateway to unlocking the full power of NumPy, the engine behind Python’s dominance in data processing, AI, and scientific computing.
Whether you're a novice or a seasoned professional, this comprehensive resource takes you on a journey from mastering the basics to understanding the most advanced features of NumPy. Imagine transforming massive datasets, running complex computations, and building sophisticated AI models—all with the unparalleled speed and efficiency that NumPy provides. And here’s where this book stands apart: AI technology is at the heart of the content, with AI-enhanced illustrations, examples, and exercises that bring even the most complex concepts to life.
The book covers essential topics such as array manipulations, matrix operations, vectorized calculations, and advanced statistical functions, all designed to enhance your understanding of data manipulation in Python. Each chapter is packed with real-world examples, hands-on exercises, and expert insights that will deepen your mastery of NumPy. From array slicing and indexing to performing statistical analysis and random matrix generation, this guide is your key to becoming a NumPy expert.
Highlights:
Comprehensive exploration of NumPy’s powerful array structures: scalars, vectors, matrices, and tensors.
Hands-on examples that mirror real-world applications, from data analysis to AI model building.
AI-generated visuals and engaging exercises that help demystify complex concepts.
Detailed chapters on essential methods like reshape(), arange(), linspace(), and more.
Advanced topics like vectorized operations, logical filtering, and aggregation functions, crucial for data-driven fields like AI and machine learning.
Whether you’re processing massive datasets or building cutting-edge AI models, this book equips you with the tools to handle it all. You’ll not only learn how to use NumPy effectively, but also gain insights into how this powerful library integrates seamlessly with other Python packages and even programming languages like C and C++.
Mastering NumPy is designed to meet you wherever you are on your data science journey and push you to new heights of efficiency, speed, and innovation. As you dive deeper, you’ll uncover how NumPy is the backbone of modern data analysis, driving performance in everything from machine learning algorithms to complex scientific computing.
Contents:
Chapter 1: Introduction to NumPy – A comprehensive look at what makes NumPy the go-to library for data manipulation in Python.
Chapter 2: What is NumPy & Installation – A guide to setting up NumPy and understanding its role in the Python ecosystem.
Chapter 3: NumPy Scalars, Vectors, Matrices, and Tensors – Exploring NumPy’s basic building blocks, from simple scalars to multi-dimensional tensors.
Chapter 4: Why Use NumPy? The Importance of NumPy – Understanding why NumPy is a must-have for efficient and powerful data manipulation.
Chapter 5: Indexing and Slicing in NumPy – Mastering the art of selecting and slicing data within arrays.
Chapter 6: NumPy Size, Shape, ndim, and dtype – Learning to navigate and modify array dimensions, shapes, and data types.
Chapter 7: Changing Data Types in NumPy - astype() and datetime64 – Working with data types and dates for greater precision in calculations.
Chapter 8: Slicing in NumPy Matrices – Delving into matrix slicing for complex data operations.
Chapter 9: NumPy Random - Generating Random Matrices – Using randomness for simulation, sampling, and testing.
Chapter 10: NumPy arange Method - Creating Ranges – Creating numerical ranges effortlessly, ideal for sequential data.
Chapter 11: NumPy linspace Method – Generating evenly spaced values for plotting and analysis.
Chapter 12: Using the NumPy reshape Method – Reshaping arrays to adapt to diverse data structures.
Chapter 13: Using the NumPy view and copy Methods – Controlling memory with views and copies for optimized performance.
Chapter 14: Using the NumPy ones, zeros, and full Methods – Creating arrays pre-filled with values to set up data structures quickly.
Chapter 15: NumPy Diagonal Methods: eye, diag, and identity – Generating diagonal matrices for specialized computations.
Chapter 16: NumPy Aggregation and Statistics – Performing data aggregation with functions like sum , mean , std , min , and max to gain insights from your data quickly.
Chapter 17: NumPy Sorting and Searching – Using functions like sort , argsort , and where to efficiently order and search within arrays, essential for data analysis.
Chapter 18: NumPy Vectorized Operations: Addition, Subtraction, Division, Multiplication, and Modulus – Harnessing the speed of vectorized operations for mathematical efficiency.
Chapter 19: Filtering and Logical Operators in NumPy Matrices – Filtering data and applying logical operations for precise data selection.
Скачать Mastering NumPy: The Ultimate Guide to Data Manipulation in Python
|
Навигация
Вход на сайт
Реклама
Mastering NumPy: The Ultimate Guide to Data Manipulation in Python 
