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Small-footprint language models trained on custom data sets and hosted locally can perform as well as large generalist models in speed and accuracy, often at a fraction of the cost. Domain-Specific Small Language Models shows you how to build privacy-preserving and regulation-compliant SLMs for agentic systems, specialist applications, and deployment on the edge.

This is a practical book that shows you how to adapt pretrained open source models to your domain using transfer learning and parameter-efficient fine-tuning. 

You just built something amazing in Python and you’re ready to share it with the world! But does shipping it to the web mean…learning JavaScript? With the Streamlit framework, you can build interactive web apps entirely in Python incredibly fast. By providing a collection of pre-built UI components and streamlined configurations, Streamlit turns your ideas for data tools and AI workflows into usable applications without any tedious HTML, CSS, and JavaScript.

Build Python Web Apps with Streamlit follows a proven learn-by-building approach. Each chapter introduces a  

Software security is about understanding how real systems fail, and how to build them so they don’t. Software Security for Developers gives you that understanding, and shows you how to apply it in the modern cloud and Kubernetes environments you work with every day.

You’ll implement secure communication channels, design authentication and identity flows, adopt passwordless approaches, and manage authorization across complex service-to-service call chains. Along the

For R programmers, the R interface to the Keras deep learning library is a powerful head start on building deep learning models without switching to Python. It provides a simple, consistent API that makes deep learning accessible and simplifies the process of building neural networks, even if you have no prior experience in advanced machine learning. 

Deep Learning with R, Third Edition introduces deep learning from scratch with examples that use the R language and the Keras library. Each chapter offers practical code examples that build your understanding