Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks.
Introducing Data Science teaches you how to accomplish the fundamental tasks that occupy data scientists. Using the Python language and common Python libraries, you'll experience firsthand the challenges of dealing with data at scale and gain a solid foundation in data science.
Certain key economic decisions taken by organizations and indeed countries are often not made by economists but by businessmen, trade unionists, politicians and policy-makers. Those who employ people, those who represent workers, those who make laws and those who elect them need economics but may have little time or desire to study...
Mathematical Statistics for Economics and Business, Second Edition, provides a comprehensive introduction to the principles of mathematical statistics which underpin statistical analyses in the fields of economics, business, and econometrics. The selection of topics in this textbook is designed to provide students with a...
Flexible, Reliable Software: Using Patterns and Agile Development guides students through the software development process. By describing practical stories, explaining the design and programming process in detail, and using projects as a learning context, the text helps readers understand why a given...
Learn how to use TensorFlow 2.0 to build machine learning and deep learning models with complete examples.
The book begins with introducing TensorFlow 2.0 framework and the major changes from its last release. Next, it focuses on building Supervised Machine Learning models using TensorFlow 2.0....
This easy-to-follow textbook teaches Java programming from first principles, as well as covering design and testing methodologies. The text is divided into two parts. Each part supports a one-semester module, the first part addressing fundamental programming concepts, and the second part building on this foundation, teaching the...
This book is intended to have three roles and to serve three associated audiences: an
introductory text on Bayesian inference star ting from first principles, a graduate text on
effective current approaches to Bayesian modeling and computation in statistics and
related fields, and a handbook of Bayesian meth ods in applied...
Modern astronomical research is beset with a vast range of statistical challenges, ranging from reducing data from megadatasets to characterizing an amazing variety of variable celestial objects or testing astrophysical theory. Linking astronomy to the world of modern statistics, this volume is a unique resource, introducing astronomers to...
The second edition of this highly praised textbook provides an introduction to tensors, group theory, and their applications in classical and quantum physics. Both intuitive and rigorous, it aims to demystify tensors by giving the slightly more abstract but conceptually much clearer definition found in the math literature, and then connects...
