Algorithms play an important role in both the science and practice of computing. To optimally use algorithms, a deeper understanding of their logic and mathematics is essential. Beyond traditional computing, the ability to apply these algorithms to solve real-world problems is a necessary skill, and this is what this book focuses on.

This book is an expert-level guide to master the neural network variants using the Python ecosystem. You will gain the skills to build smarter, faster, and efficient deep learning systems with practical examples. By the end of this book, you will be up to date with the latest advances and current researches in the deep learning domain.

A second edition of the bestselling guide to exploring and mastering deep learning with Keras, updated to include TensorFlow 2.x with new chapters on object detection, semantic segmentation, and unsupervised learning using mutual information.

Python comes with a plethora of tools that enable you to create high-performance and robust programs. This book will help you explore these tools to take your programs to the next level by introducing a myriad of advanced functionalities and providing practical knowledge of how to apply them to your own use cases.

The Agile Model-Based Systems Engineering Cookbook distills the most relevant MBSE workflows and work products into a set of easy-to-follow recipes, complete with examples of their application. This book serves as a quick and reliable practical reference for systems engineers looking to apply agile MBSE to real-world projects.

Unlock the power of AI and become a successful product manager with this comprehensive guide covering the strategies, techniques, and tools to build, launch, and manage AI products. From the basics of AI to navigating ethical and legal considerations, this book covers everything you need to know to drive product development and growth in the AI industry.

This book will take you on a journey from an idea ("buy bullish stocks, sell bearish ones") to becoming part of the elite club of long/short algorithmic traders. Along the way, we will explore several key concepts, such as trading edge, frequency, signal processing, trading psychology, capital efficiency, risk management, and asset allocation, one stumbling block at a time.