Deep Learning

Master language models through mathematics, illustrations, and code―and build your own from scratch!

A clear, illustrated guide to large language models, covering key concepts and practical applications. Ideal for projects, interviews, or personal learning.

Turn data into decisions. Data Visualization Using Tableau for Data Scientists shows how interactive visuals, analytics, and storytelling come together to make complex data understandable, actionable, and impactful.

It's never been easier to build an AI agent — and never been harder to make one that actually works. This book takes you from language model foundations to production-ready multi-agent systems with the depth to predict failure before it happens, engineer graceful degradation over catastrophic failure, and take absolute architectural ownership. Get the paperback from amazon.

A practical guide to fine-tuning Large Language Models (LLMs), offering both a high-level overview and detailed instructions on how to train these models for specific tasks.Get the paperback version here. Get the Kindle version here.

Revised for PyTorch 2.x! In 2019, I published a PyTorch tutorial on Towards Data Science and I was amazed by the reaction from the readers! Their feedback motivated me to write this book to help beginners start their journey into Deep Learning and PyTorch. I hope you enjoy reading this book as much as I enjoy writing it.

Documentation isn’t just a chore—it’s a craft. And with AI tools at your side, it’s finally scalable, smart, and developer-friendly. Document Like a Developer: Technical Writing with AI Tools is your blueprint for building docs that ship with your code, evolve with your product, and speak your users’ language. Learn how to enforce style guides, automate glossary checks, run documentation sprints, and measure impact with precision. Whether you're a solo dev, a startup team, or scaling across an enterprise, this book gives you the workflows, templates, and mindset to treat documentation like a first-class citizen. Stop writing throwaway manuals. Start building living systems of clarity. The future of technical writing is here—and it’s automated, collaborative, and built for velocity.

Why This Book Is Unique·        Focused specifically on data science applications of SQL, not just traditional database operations.·        Includes Python integration, bridging database skills with modern data analysis.·        Covers NoSQL and unstructured data, expanding student exposure beyond relational databases.·        Emphasizes real datasets, case studies, and hands-on exercises, making learning interactive and practical.·        Prepares students for academic projects, internships, and entry-level data science roles.  

Every deep learning tutorial shows you the code. Almost none show you the idea. This is the book to read first - before the frameworks, before the maths notation, before the course you've already paid for. One example, followed all the way through, from a random guess to a network that works. By the end you'll understand what backpropagation actually does, why gradients matter, and what's really happening while your model trains. No calculus required.

This book is a quick foray into the world of deep learning-based computer vision and abnormal equipment sound detection. The readers are introduced to the ease with which powerful equipment and product quality monitoring solutions can be built using sound and visual data.

Master deep learning with PyTorch & Lightning. Core concepts, practical Q&A, and production-ready code with a full companion GitHub repository.

Понятный иллюстрированный путеводитель по ключевым концепциям и практическим применениям больших языковых моделей. Идеально подходит для работы над проектами, подготовки к собеседованиям и самостоятельного обучения.

هذا الكتاب هو دليل مختصر وموضّح بالرسوم لأي شخص يرغب في فهم الآلية الداخلية للنماذج اللغوية الضخمة، سواء في سياق المقابلات أو المشاريع أو بدافع الفضول الشخصي.

A machine can hand you a grouping that is confident, stable, internally consistent, and seven times worse than the one it found a moment earlier. Nothing in the output says so.This book works k-means through completely on twelve bakery customers, small enough that every number is printed and checkable. You will build the method from nothing, see exactly where it succeeds, and see exactly where it fails silently.Fifty-eight figures, every one captured from a running implementation.

Build a world-class technical publishing brand with this complete guide to designing, structuring, and publishing professional Tech Capsules. Learn proven layouts, visual identity, content architecture, publishing workflows, and best practices used to create high-quality technical micro-books that readers lov