As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to basic machine learning concepts and incorporate that knowledge into Angular applications. The book is intended to be a fast-paced introduction to some basic features of machine learning and an overview of several popular machine learning classifiers. It includes code samples and numerous figures and covers topics such as Angular functionality, basic machine learning concepts, classification algorithms, TensorFlow and Keras. The files with code and color figures are on the companion disc with the book or available from the publisher. Features: Introduces the basic machine learning concepts and Angular applications Includes source code and full color figures

As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to basic deep learning concepts and incorporate that knowledge into Angular 10 applications. It is intended to be a fast-paced introduction to some basic features of deep learning and an overview of several popular deep learning classifiers. The book includes code samples and numerous figures and covers topics such as Angular 10 functionality, basic deep learning concepts, classification algorithms, TensorFlow, and Keras. Companion files with code and color figures are included. FEATURES: Introduces basic deep learning concepts and Angular 10 applications Covers MLPs (MultiLayer Perceptrons) and CNNs (Convolutional Neural Networks), RNNs (Recurrent Neural Networks), LSTMs (Long Short-Term Memory), GRUs (Gated Recurrent Units), autoencoders, and GANs (Generative Adversarial Networks) Introduces TensorFlow 2 and Keras Includes companion files with source code and 4-color figures. The companion files are also available online by emailing the publisher with proof of purchase at [email protected].

This book provides readers with enough information for them to develop more sophisticated Angular applications that incorporate deep learning. The first three chapters of this book contain a short tour of basic Angular functionality, such as UI components and forms in Angular applications. The fourth chapter introduces you to deep learning, the problems it can solve, and some challenges for the future. You will also learn about MLPs (MultiLayer Perceptrons), CNNs (Convolutional Neural Networks), and a Keras-based code sample of a CNN with the MNIST dataset. The fifth chapter discusses RNNs (Recurrent Neural Networks), BPTT (Back Propagation Through Time), as well as LSTMs (Long Short Term Memory) and AEs (Auto Encoders). The sixth chapter introduces basic TensorFlow concepts, followed by tensorflowjs (i.e., TensorFlow in modern browsers), and some examples of Angular applications combined with deep learning.

As part of the best-selling Pocket Primer series, this book provides an overview of the major aspects and the source code to use the latest versions of Angular 4. It has coverage of the fundamental aspects of Angular that are illustrated via numerous code samples. This Pocket Primer is primarily for self-directed learners who want to learn Angular 4 programming, and it serves as a starting point for deeper exploration of its numerous applications. A companion disc (also available for downloading from the publisher) with source code and color images is included. FEATURES • Contains latest material on Angular 4, graphics/animation, mobile apps, • Includes companion files with all of the source code and images from the book • Provides coverage of the fundamental aspects of Angular4 that are illustrated via code samples BRIEF TABLE OF CONTENTS 1. A Quick Introduction to Angular. 2. UI Controls and User Input. 3. Graphics and Animation. 4. HTTP Requests and Routing. 5. Forms, Pipes, and Services. 6. Angular and Express. 7. Flux, Redux, GraphQL, Apollo, and Relay. 8. Angular and Mobile Apps. 9. Functional Reactive Programming. 10. Miscellaneous Topics. Index. ON THE COMPANION FILES! • Hundreds of source code samples • All images from the text (including 4-color) eBook Customers: Companion files are available for downloading with order number/proof of purchase by writing to the publisher at [email protected].

Amid an unprecedented digital revolution, our society grapples with profound challenges, from the upheaval of traditional global systems to the ethical implications of technology's inexorable advance. As academic scholars seek a comprehensive understanding of this dynamic environment, Driving Decentralization and Disruption With Digital Technologies emerges as a beacon of insight. This compelling book confronts the intricate issues spawned by decentralization, de-globalization, and the transformative power of digital technologies, providing a roadmap for traversing the complexities of our digitally connected world. The book starts by unraveling the disruptive forces at play, shedding light on the threats posed to existing hierarchies and the potential consequences for disadvantaged groups. Digital disintermediation, driven by platforms and peer-to-peer networks, shakes the foundations of traditional economic systems, leaving banks and markets in flux. As global relationships redefine themselves in the face of decentralized markets, supply chains, and economic ties, scholars grapple with the profound implications for the future.

This book begins with an introduction to AI, followed by machine learning, deep learning, NLP, and reinforcement learning. Readers will learn about machine learning classifiers such as logistic regression, k-NN, decision trees, random forests, and SVMs. Next, the book covers deep learning architectures such as CNNs, RNNs, LSTMs, and auto encoders. Keras-based code samples are included to supplement the theoretical discussion. In addition, this book contains appendices for Keras, TensorFlow 2, and Pandas. Features: Covers an introduction to programming concepts related to AI, machine learning, and deep learning Includes material on Keras, TensorFlow2 and Pandas

The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. ... Summing Up: Highly recommended. F. H. Wild III, Choice, Vol. 47 (8), April 2010 Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.” John D. Cook, The Mathematical Association of America, September 2011 This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science. Alex Small, IEEE, CiSE Vol. 14 (2), March /April 2012 “This fourth edition is a wonderful, inclusive textbook that covers pretty much everything one needs to know to go from zero to fairly sophisticated scientific programming in Python...” Joan Horvath, Computing Reviews, March 2015