Books

Benefits of Studying This Book 1. Deep Conceptual Understanding You will understand why AI algorithms work, not just how to run them. This allows you to innovate, debug, and improve models. 2. Career Advantage Strong mathematical foundations make you stand out in interviews for AI, ML, and DS roles. Many recruiters test candidates on linear algebra and probability skills. 3. Research Readiness Postgraduate students and researchers can directly apply these mathematical tools to design and analyze experiments. 4. Practical AI Skills Python-based implementation examples ensure that you can directly apply mathematical concepts in real-world AI systems. 5. Interdisciplinary Edge Mathematics learned here is not limited to AI — it can be applied in robotics, quantum computing, finance, bioinformatics, and more. How This Book Helps After StudyAfter completing this book, you will be able to:·        Build AI models from scratch, knowing exactly what mathematical operations are happening inside.·        Optimize models for performance using a deep understanding of linear algebra operations.·        Analyze and interpret model predictions probabilistically.·        Handle uncertainty and noise in datasets effectively.·        Implement advanced AI concepts like PCA, SVD, Bayesian inference, and Markov models without relying solely on pre-built libraries.This knowledge will directly help in:·        Academics: Scoring well in AI/ML/DS university courses.·        Industry: Working as an AI engineer, data scientist, ML engineer, or research scientist.·        Competitive Exams: Preparing for GATE, NET, and other AI-related exams where mathematics is heavily tested.·        Research: Publishing papers where mathematical rigor is required to explain new AI techniques. 

A Sample Learning Journey with This Book Imagine a final-year MCA student who needs to select a project topic.·        After Chapter-3, they can identify a novel, research-worthy problem.·        By Chapter-5, they will know how to collect, clean, and preprocess relevant data.·        Using Chapter-6 and 8, they can implement a fair and unbiased ML model.·        Through Chapter-9 and 10, they can interpret results with statistical confidence.·        By Chapter-11, they will have the skills to write a publication-ready paper.In short, the book transforms a student project into publishable research.

Il giudizio non si delega. Il perimetro entro cui l'agente si muove, la verifica che deve passare, la condizione che lo ferma: quelli sì. Come un Senior trasforma vent'anni di mestiere nei vincoli che governano un agente, e come decisioni, criteri e lezioni restano quando la sessione finisce: è l'amplificazione del titolo.

Unlock the power of Cyclical AI and move beyond linear chains with LangGraph.js. This deep-dive guide teaches TypeScript developers to build autonomous agents that can reason, loop, self-correct, and collaborate. Master the architecture of stateful, multi-agent systems, from advanced state management to production deployment. Stop building scripts and start engineering the intelligent, resilient systems of the future.

Stop Watching the Market. Start Coding It. 📈 Welcome to the era of "Quantamental" AI Trading. Volume 7 is your engineering manual for building professional-grade trading infrastructure. Bridge the gap between classical technical analysis and LLMs—designing systems that trade on both Math (price action) and News (sentiment). From vectorized backtesting to sentiment analysis with FinBERT, it’s time to engineer your edge.

Holistic testing is a comprehensive term to encompass testing throughout the development cycle from the start of an idea, through to customer interaction with a delivered feature. All members of a delivery team think about testing and quality from the beginning and throughout the cycle.  This book is about the Holistic Testing Model and how to apply it to develop a quality and testing strategy for the whole team. If you care about quality – no matter what your specialty or role in your organization is – we think you’ll find it helpful. UI/UX designers, product owners, programmers, testers, database experts, business analysts, site reliability and platform engineers, and more – this model will guide you as you collaborate to continually improve your process and product. 

Read this book to learn about different factors influencing the size of your C++ binaries. You'll discover how different ways of coding can increase or decrease binary sizes. We'll look into which compiler and linker settings significantly impact sizes. Last but not least, we'll look into the intersection of coding techniques and compiler settings.

2025 edition! Brought to you by best-selling author and global training guru Nigel Poulton, Getting Started with Docker is the fastest way to wrap your head around Docker and AI. It's packed with hands-on examples, including a multi-container chatbot app that integrates with Docker Model Runner for local AI. When you've finished the book, you'll be ready to use Docker in real-world projects.

Become a better data scientist by understanding different modeling mindsets.

The Expert Curve is about how expertise is achieved. With a comprehensive look into the science behind expertise, talent, prodigies, and training, The Expert Curve lays out the current understanding of how people learn to operate at expert levels in their fields and gives you the best tools to achieve expertise yourself.

This 2025 edition of Quick Start Kubernetes is bang up to date with the latest versions of Kubernetes and industry trends. Brought to you by best-selling author and global training guru Nigel Poulton, Quick Start Kubernetes is the fastest way to wrap your head around Kubernetes and get your hands on deploying a simple app. When you've finished the book, you'll be ready to use Kubernetes in the real world.

SAP Data Medium Exchange by Techlorean. Simple Explanation + Quick Understanding. Expect a casual non-technical tone to help you understand the subject matter rather than just knowing the configurations.

O Management 3.0, escrito por Jurgen Apello, mostra uma nova abordagem para tratar o gerenciamento em tempos de agilidade e constantes mudanças. Nesse livro estão sintetizadas as principais ideias com um pouco da minha experiência.

Can you build a script to count the number of sequences in a Big data consisting hundred thousands of nucleotide sequences in 30 seconds? You may wonder to know, this wouldn't take more a than a few words in Bash "grep -c "^>" data.fa" ! This book will help you to become an expert in bash and learn to explore real-world large data sets.

Long regarded as one of the first books to pioneer a people-oriented approach to computing, The Psychology of Computer Programming endures as a penetrating analysis of the intelligence, skill, teamwork, and problem-solving power of the computer programmer.