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

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First published: June 2018

Production reference: 1270618

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ISBN 978-1-78899-335-7

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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.

Tiago Antao is a computer scientist turned computational biologist with a PhD from Liverpool School of Tropical Medicine in UK. He is a co-author of Biopython, a major bioinformatics package written in Python.

In his career he has worked at University of Cambridge (UK) and University of Oxford (UK), and is currently a research scientist at University of Montana (USA). He is the author of Bioinformatics with Python Cookbook.

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If you are trying to hone your skills in the field of data science, there are many books and courses out there with varying levels of difficulty. What usually happens is that you start to study introductory resources and then continue with more in-depth, technical ones to get a taste of a new field or technology. If you were following this kind of learning path for sometime, you must have realized that it becomes very time consuming journey. We, as lifelong learners, need books with more compact representation of knowledge and experience which requires the right balance between theory and practice. This book aims to bring beginner, intermediate, and advanced concepts together and it is our humble effort to build up your knowledge from scratch.

This book assumes no previous background of scientific computing and will introduce various subjects using practical examples. It may sometimes feel like separate topics pulled together randomly and the book's flow doesn't stick to one consistent path. This was a deliberate decision we made to give you a little taste of several different topics and applications.

We hope that you will read this book to have a broader overview of scientific computing as well as to master the nitty-gritty of NumPy and other supporting scientific libraries of Python such as SciPy and Scikit-Learn.

This book is for everyone who would like to gain additional knowledge in the data science field. Mastering Numerical Computing with NumPy is for you if you are a Python programmer, data analyst, data engineer, or 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.