Bundles

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Combinatorial Thinking in Artificial Intelligence: Permutation Logic, State-Space Optimization, and Algorithmic Design (Complete Bundle Edition) reveals the mathematical foundations behind intelligent search, optimization, planning, machine learning, and algorithmic reasoning.From permutations, combinations, graph theory, and state-space modeling to heuristic search, neural architecture optimization, constraint satisfaction, quantum search, and generative AI, this two-volume collection provides a comprehensive roadmap to understanding how modern AI systems think, search, and optimize.Ideal for students, researchers, software engineers, AI practitioners, and algorithm designers seeking a deeper understanding of the hidden combinatorial structures that power intelligent systems.

Get Interpretable Machine Learning (2nd edition), Modeling Mindsets, and Introduction to Conformal Prediction.

Get Interpretable Machine Learning (2nd edition), Modeling Mindsets, and Introduction to Conformal Prediction.

All the books on data journalism by Paul Bradshaw. This includes:Data Journalism Heist - a quick introduction to the most important spreadsheet techniques for finding stories against a deadlineFinding Stories in Spreadsheets - takes you through dozens of spreadsheet techniques for a range of data journalism scenarios, including finding stories,...

All the books on data journalism by Paul Bradshaw. This includes:Data Journalism Heist - a quick introduction to the most important spreadsheet techniques for finding stories against a deadlineFinding Stories in Spreadsheets - takes you through dozens of spreadsheet techniques for a range of data journalism scenarios, including finding stories,...

Stop building fragile AI toys. Master the complete engineering stack for production-grade LLMs, vector search, high-performance inference, and autonomous AI agents.​LLM Engineering, AI Architecture, Agentic AI, Semantic Search, Vector Databases, AI Infrastructure, Python Performance, Machine Learning Systems, DevOps for AI, RAG Pipelines

Don't panic. Drink coffee, code stuff, sell things online, and let AI pay the bills. 0% fluff, 100% human-approved. Understand AI over coffee ☕Vibecode a business from your couch 🛋️Make money on KDP without talking to people 🤫(Repeat until wealthy or rescued).

What is intelligence?At its core, intelligence is the ability to acquire, compress, transform, communicate, and generate information.The Information Theory and Artificial Intelligence Complete Series explores the mathematical foundations that power modern machine learning, deep learning, generative AI, reinforcement learning, and large language models.Inside this two-volume series, you'll discover:✓ Shannon Entropy and Information Measures✓ Mutual Information and Representation Learning✓ Cross-Entropy and KL Divergence✓ Data Compression and Coding Theory✓ Information Bottleneck Theory✓ Variational Autoencoders (VAEs)✓ Contrastive and Self-Supervised Learning✓ Generative Adversarial Networks (GANs)✓ Entropy-Driven Reinforcement Learning✓ Fisher Information and Information Geometry✓ Information Theory Behind Transformers and LLMs✓ Federated Learning and Distributed Intelligence✓ Explainable AI Through Entropy✓ Quantum Information Theory✓ AI Fairness, Safety, Alignment, and Future ResearchWhether you are learning information theory for the first time or exploring the mathematical foundations of advanced AI systems, this bundle provides the tools, theory, and insights needed to understand how information becomes intelligence.Learn not just how AI works—but why it works.

Four volumes. 76 chapters. 2,000+ pages. The complete data-engineering arc from your first spark.read.csv to a production multi-agent system on Databricks, written for the engineer who gets paged when the pipeline breaks at 2 a.m.

How do machines predict future outcomes? Why do some models generalize well while others fail? How can AI systems estimate uncertainty, explain their predictions, and operate reliably in real-world environments?Linear and Nonlinear Regression in Artificial Intelligence: Mathematical Foundations, Regularization Techniques & Predictive Modeling (Complete Bundle Edition) provides a comprehensive exploration of predictive intelligence—from classical linear regression to advanced Bayesian models, Gaussian Processes, neural network regression, kernel methods, explainable AI, and large-scale machine learning systems.Combining mathematical rigor, practical machine learning techniques, real-world case studies, and modern AI applications, this two-volume collection equips readers with the knowledge required to design, evaluate, interpret, and deploy predictive models across healthcare, finance, engineering, business analytics, scientific research, and next-generation AI systems.Whether you are a student, researcher, data scientist, or AI professional, this bundle offers a complete roadmap to mastering the science of prediction.