The.Hottest

A. C. Faul ... 334 pages - Language: English - Publisher: Chapman and Hall/CRC; (August, 2019) - AmazonSIN: ‎B07VYV4NLM.


The emphasis of the book is on the question of Why – only if why an algorithm is successful is understood, can it be properly applied, and the results trusted. Algorithms are often taught side by side without showing the similarities and differences between them. This book addresses the commonalities, and aims to give a thorough and in-depth treatment and develop intuition, while remaining concise. This useful reference should be an essential on the bookshelves of anyone employing machine learning techniques.

Franz Kronthaler ... 367 pages - Language: English - Publisher: ‎Springer; (November, 2022) - ISBN-10: 3662643189 - ISBN-13: 978-3662643181.


This book shows you how to analyze data sets systematically and to use Excel 2019 to extract information from data almost effortlessly. Both are (not) an art! The statistical methods are presented and discussed using a single data set. This makes it clear how the methods build on each other and gradually more and more information can be extracted from the data. The Excel functions used are explained in detail - the procedure can be easily transferred to other data sets. 

Various didactic elements facilitate orientation and working with the book: At the checkpoints, the most important aspects from each chapter are briefly summarized. In the freak knowledge section, more advanced aspects are addressed to whet the appetite for more. All examples are calculated with hand and Excel. Numerous applications and solutions as well as further data sets are available on the author's internet platform.

Jonathan Schwabish ... 384 pages - Language: English - Publisher: A.K. Peters/CRC Press; (May, 2023) - ISBN-10: ‎1032343265 - ISBN-13: ‎978-1032343266.

This book closes the gap between what people think Excel can do and what they can achieve in the tool. Over the past few years, recognition of the importance of effectively visualizing data has led to an explosion of data analysis and visualization software tools. But for many people, Microsoft Excel continues to be the workhorse for their data visualization needs, not to mention the only tool that many data workers have access to. Although Excel is not a specialist data visualization platform, it does have strong capabilities. The default chart types do not need to be the limit of the tool’s data visualization capabilities, and users can extend its features by understanding some key elements and strategies.

Data Visualization in Excel provides a step-by-step guide to creating more advanced and often more effective data visualizations in Excel and is the perfect guide for anyone who wants to create better, more effective, and more engaging data visualizations.

Shuvra Das ... 313 pages - Language: ‎English - Publisher: ‎Springer (March, 2023) - AmazonSIN: ‎ B0BSF5M5RL.

This book is an attempt to develop a guide for the user who is interested in learning the method by doing. There is enough discussion of some of the basic theory so that the user can get a broad understanding of the process. And there are many examples with step-by-step instructions for the user to quickly develop some proficiency in using FEA. We have used Matlab and its PDE toolbox for the examples in this text. The syntax and the modeling process are easy to understand and a new user can become productive very quickly. The PDE toolbox, just like any other commercial software, can solve certain classes of problems well but is not capable of solving every type of problem. For example, it can solve linear problems but is not capable of handling non-linear problems. Being aware of the capabilities of any tool is an important lesson for the user and we have, with this book, tried to highlight that lesson as well.

Joseph Tranquillo ... 189 pages - Language: ‎English - Publisher:‎ Springer; 2nd edition (March, 2023) - AmazonSIN: ‎B0BW3RK1Z8.


This book is a self-guided tour of MATLAB for engineers and life scientists. It introduces the most commonly used programming techniques through biologically inspired examples. Although the text is written for undergraduates, graduate students and academics, as well as those in industry, will find value in learning MATLAB.

The book takes the emphasis off of learning syntax so that the reader can focus more on algorithmic thinking. Although it is not assumed that the reader has taken differential equations or a linear algebra class, there are short introductions to many of these concepts. Following a short history of computing, the MATLAB environment is introduced. Next, vectors and matrices are discussed, followed by matrix-vector operations. The core programming elements of MATLAB are introduced in three successive chapters on scripts, loops, and conditional logic. The last three chapters outline how to manage the input and output of data, create professional quality graphics and find and use MATLAB toolboxes. Throughout, biomedical and life science examples are used to illustrate MATLAB's capabilities.

Focuses the reader on algorithmic thinking and not on the learning of syntax; Emphasizes the foundations and ability to efficiently integrate and operate vectors and matrices; Demonstrates MATLAB as a powerful all-purpose application tool concentrating on the idea of a script and then the concept of a function.

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