logo

EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link:  https://ebookbell.com/faq 


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

Just Enough Data Science And Machine Learning Essential Tools And Techniques Mark Levene Martyn Harris

  • SKU: BELL-77569614
Just Enough Data Science And Machine Learning Essential Tools And Techniques Mark Levene Martyn Harris
$ 31.00 $ 45.00 (-31%)

4.7

16 reviews

Just Enough Data Science And Machine Learning Essential Tools And Techniques Mark Levene Martyn Harris instant download after payment.

Publisher: Addisonn-Wesley
File Extension: EPUB
File size: 9.33 MB
Pages: 224
Author: Mark Levene & Martyn Harris
ISBN: 9780138340773, 0138340773
Language: English
Year: 2024

Product desciption

Just Enough Data Science And Machine Learning Essential Tools And Techniques Mark Levene Martyn Harris by Mark Levene & Martyn Harris 9780138340773, 0138340773 instant download after payment.

An accessible introduction to applied data science and machine learning, with minimal math and code required to master the foundational and technical aspects of data science.

In Just Enough Data Science and Machine Learning, authors Mark Levene and Martyn Harris present a comprehensive and accessible introduction to data science. It allows the readers to develop an intuition behind the methods adopted in both data science and machine learning, which is the algorithmic component of data science involving the discovery of patterns from input data. This book looks at data science from an applied perspective, where emphasis is placed on the algorithmic aspects of data science and on the fundamental statistical concepts necessary to understand the subject.

The book begins by exploring the nature of data science and its origins in basic statistics. The authors then guide readers through the essential steps of data science, starting with exploratory data analysis using visualisation tools. They explain the process of forming hypotheses, building statistical models, and utilising algorithmic methods to discover patterns in the data. Finally, the authors discuss general issues and preliminary concepts that are needed to understand machine learning, which is central to the discipline of data science.

The book is packed with practical examples and real-world data sets throughout to reinforce the concepts. All examples are supported by Python code external to the reading material to keep the book timeless.

Notable features of this book

Clear explanations of fundamental statistical notions and concepts

Coverage of various types of data and techniques for analysis

In-depth exploration of popular machine learning tools and methods

Insight into specific data science topics, such as social networks and sentiment analysis

Practical examples and case studies for real-world application

Recommended further reading for deeper exploration of specific topics.

Related Products