This is the code repository for Mastering Numerical Computing with NumPy, published by Packt.
Master scientific computing and perform complex operations with ease
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.
This book covers the following exciting features:
- 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
If you feel this book is for you, get your copy today!
All of the code is organized into folders. For example, Chapter02.
The code will look like the following:
'sepal width (cm)', 'petal length (cm)', 'petal width (cm)'])
Following is what you need for this book: 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.
With the following software and hardware list you can run all code files present in the book (Chapter 1-9).
| Chapter | Software required | OS required |
|---|---|---|
| 1-9 | Anaconda distribution of Python 3 | Windows, Mac OS X, and Linux (Any) |
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.
Umit Mert Cakmak is a data scientist at IBM, where he excels at helping clients solve complex data science problems, from inception to delivery of deployable assets. His research spans multiple disciplines beyond his industry and he likes sharing his insights at conferences, universities, and meet-ups.
Mert Cuhadaroglu is a BI Developer in EPAM, developing E2E analytics solutions for complex business problems in various industries, mostly investment banking, FMCG, media, communication, and pharma. He consistently uses advanced statistical models and ML algorithms to provide actionable insights. Throughout his career, he has worked in several other industries, such as banking and asset management. He continues his academic research in AI for trading algorithms.
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