AI Books

As Python continues to grow in popularity, projects are becoming larger and more complex. Many Python developers are taking an interest in high-level software design patterns such as hexagonal/clean architecture, event-driven architecture, and the strategic patterns prescribed by domain-driven design (DDD). But translating those patterns into Pytho

Deep learning has transformed the fields of computer vision, image processing, and natural language applications. Thanks to TensorFlow.js, now JavaScript developers can build deep learning apps without relying on Python or R. Deep Learning with JavaScript shows developers how they can bring DL technology to the web. Written by the main authors of t

There is currently no comprehensive scientific study that addresses the problem of financing projects using Distributed Ledger (blockchain) Technology (DLT) that are not themselves embedded in the blockchain ecosystem, particularly in the context of long-term and capital-intensive investments. This book fills this gap. It poses a number of research

Games have long been excellent benchmarks for AI algorithms for two reasons. Initially, games are developed to assess and challenge human intelligence, and the variety of games can provide a rich context for evaluating different cognitive and decision-making abilities. Secondly, addressing complex real-world challenges often requires repeated trial

AI is transforming numerous industries. Machine Learning Yearning, a free ebook from Andrew Ng, teaches you how to structure Machine Learning projects. This book is focused not on teaching you ML algorithms, but on how to make ML algorithms work. After reading Machine Learning Yearning, you will be able to: - Prioritize the most promising direction

This unique open access volume represents an interdisciplinary dialog with top-class researchers and practitioners on the Artificial Intelligence revolution. The contributions derive from structured interviews with community leaders who examine recent developments in AI and offer predictions about its impact on science, technology, business, and so

This guide is an introduction to developing microservices-based applications and managing them using containers. It discusses architectural design and implementation approaches using .NET Core and Docker containers. To make it easier to get started with containers and microservices, the guide focuses on a reference containerized and microservice-ba

As the software development landscape evolves, the challenge of managing and refactoring extensive code bases becomes increasingly complex. AI methods of code refactoring, while effective for smaller scales, can falter under the weight of mass-scale operations. The need for efficiency, accuracy, and consistency is more critical than ever. This key

With the introduction of container support in Windows Server, we open a world of opportunities that takes traditional monolithic applications on a journey to modernize them for better agility. Containers are a stepping stone that can help IT organizations understand what key items in modern IT environments, such as DevOps, Agile, Scrum, Infrastruct

AI coding assistants are helping teams create software faster than ever. But to turn that speed into real innovation, organizations must go beyond writing code and deliver software quickly, securely, and reliably. While AI-assisted coding is now mainstream, what happens after the code is written is still catching up. AI-Native Software Delivery is