
Mathematics of Machine Learning
May 2025 | 730 pages
Introduction
Part 1: Linear Algebra
1 Vectors and Vector Spaces
2 The Geometric Structure of Vector Spaces
3 Linear Algebra in Practice
4 Linear Transformations
5 Matrices and Equations
6 Eigenvalues and Eigenvectors
7 Matrix Factorizations
8 Matrices and Graphs
References
Part 2: Calculus
9 Functions
10 Numbers, Sequences, and Series
11 Topology, Limits, and Continuity
12 Differentiation
13 Optimization
14 Integration
References
Part 3: Multivariable Calculus
15 Multivariable Functions
16 Derivatives and Gradients
17 Optimization in Multiple Variables
References
Part 4: Probability Theory
18 What is Probability?
19 Random Variables and Distributions
20 The Expected Value
References
Part 5: Appendix
Other Books You May Enjoy
Index
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Building Agentic AI Systems
April 2025 | 288 pages
Part 1: Foundations of Generative AI and Agentic Systems
Chapter 1: Fundamentals of Generative AI
Chapter 2: Principles of Agentic Systems
Chapter 3: Essential Components of Intelligent Agents
Part 2: Designing and Implementing Generative AI-Based Agents
Chapter 4: Reflection and Introspection in Agents
Chapter 5: Enabling Tool Use and Planning in Agents
Chapter 6: Exploring the Coordinator, Worker, and Delegator Approach
Chapter 7: Effective Agentic System Design Techniques
Part 3: Trust, Safety, Ethics, and Applications
Chapter 8: Building Trust in Generative AI Systems
Chapter 9: Managing Safety and Ethical Considerations
Chapter 10: Common Use Cases and Applications
Chapter 11: Conclusion and Future Outlook
Index
Other Books You May Enjoy
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LLM Engineer's Handbook
October 2024 | 522 pages
Understanding the LLM Twin Concept and Architecture
Tooling and Installation
Data Engineering
RAG Feature Pipeline
Supervised Fine-Tuning
Fine-Tuning with Preference Alignment
Evaluating LLMs
Inference Optimization
RAG Inference Pipeline
Inference Pipeline Deployment
MLOps and LLMOps
MLOps Principles
Other Books You May Enjoy
Index
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Building AI Agents with LLMs, RAG, and Knowledge Graphs
July 2025 | 560 pages
Part 1:
The AI Agent Engine: From Text to Large Language Models
Chapter 1: Analyzing Text Data with Deep Learning
Chapter 2: The Transformer: The Model Behind the Modern AI Revolution
Chapter 3: Exploring LLMs as a Powerful AI Engine
Part 2:
AI Agents and Retrieval
of Knowledge
Chapter 4: Building a Web Scraping Agent with an LLM
Chapter 5: Extending Your Agent with RAG to Prevent Hallucinations
Chapter 6: Advanced RAG Techniques for Information Retrieval and Augmentation
Chapter 7: Creating and Connecting a Knowledge Graph to an AI Agent
Chapter 8: Reinforcement Learning and AI Agents
Part 3:
Creating Sophisticated AI to Solve Complex Scenarios
Chapter 9: Creating Single- and Multi-Agent Systems
Chapter 10: Building an AI Agent Application
Chapter 11: The Future Ahead
Index
Other Books You May Enjoy
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Machine Learning Product Management - Strategy to Deployment
August 2025 | 285 pages
Getting Started with Machine Learning
Decision Criteria for Machine Learning Implementation
Managing Machine Learning Projects
Data Acquisition and Preparation for Machine Learning
Preprocessing Techniques for Machine Learning
Algorithm Selection and ML Solution Development
Model Evaluation Metrics and Performance Optimization
ML Model Deployment and Monitoring
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Generative AI with LangChain
May 2025 | 480 pages
The Rise of Generative AI: From Language Models to Agents
First Steps with LangChain
Building Workflows with LangGraph
Building Intelligent RAG Systems
Building Intelligent Agents
Advanced Applications and Multi-Agent Systems
Software Development and Data Analysis Agents
Evaluation and Testing
Production-Ready LLM Deployment and Observability
The Future of Generative Models: Beyond Scaling
Other Books You May Enjoy
Index
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AI Engineer Explorer Course
July 2025 | 761 pages
Introduction to Course and Instructor
Python Programming Basics for Artificial Intelligence
Data Science Essentials for Artificial Intelligence
Mathematics for Machine Learning and Artificial Intelligence
Probability and Statistics for Machine Learning and Artificial Intelligence
Introduction to Machine Learning
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Graph Machine Learning
July 2025 | 434 pages
Part 1: Introduction to Graph Machine Learning
Getting Started with Graphs
Graph Machine Learning
Neural Networks and Graphs
Part 2: Machine Learning on Graphs
Unsupervised Graph Learning
Supervised Graph Learning
Solving Common Graph-Based Machine Learning Problems
Part 3: Practical Applications of Graph Machine Learning
Social Network Graphs
Text Analytics and Natural Language Processing Using Graphs
Graph Analysis for Credit Card Transactions
Building a Data-Driven Graph-Powered Application
Part 4: Advanced topics in Graph Machine Learning
Temporal Graph Machine Learning
GraphML and LLMs
Novel Trends on Graphs
Index
Other Books You May Enjoy
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Building Business-Ready Generative AI Systems
July 2025 | 444 pages
Defining a Business-Ready Generative AI System
Building the Generative AI Controller
Integrating Dynamic RAG into the GenAISys
Building the AI Controller Orchestration Interface
Adding Multimodal, Multifunctional Reasoning with Chain of Thought
Reasoning E-Marketing AI Agents
Enhancing the GenAISys with DeepSeek
GenAISys for Trajectory Simulation and Prediction
Upgrading the GenAISys with Data Security and Moderation for Customer Service
Presenting Your Business-Ready Generative AI System
Answers
Other Books You May Enjoy
Index
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C++ in Embedded Systems
July 2025 | 402 pages
Part I: Introduction to C++ in Embedded Development
Debunking Common Myths about C++
Challenges in Embedded Systems with Limited Resources
Embedded C++ Ecosystem
Setting Up the Development Environment for a C++ Embedded Project
Part II: C++ Fundamentals
Classes – Building Blocks of C++ Applications
Beyond Classes – Fundamental C++ Concepts
Strengthening Firmware – Practical C++ Error Handling Methods
Part III: C++ Advanced Concepts
Building Generic and Reusable Code with Templates
Improving Type-Safety with Strong Types
Writing Expressive Code with Lambdas
Compile-Time Computation
Part IV: Applying C++ to Solving Embedded Domain Problems
Writing C++ HAL
Working with C Libraries
Enhancing Super-Loop with Sequencer
Practical Patterns – Building a Temperature Publisher
Designing Scalable Finite State Machines
Libraries and Frameworks
Cross-Platform Development
Other Books You May Enjoy
Index
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Python Machine Learning By Example
July 2024 | 526 pages
Getting Started with Machine Learning and Python
Building a Movie Recommendation Engine with Naïve Bayes
Predicting Online Ad Click-Through with Tree-Based Algorithms
Predicting Online Ad Click-Through with Logistic Regression
Predicting Stock Prices with Regression Algorithms
Predicting Stock Prices with Artificial Neural Networks
Mining the 20 Newsgroups Dataset with Text Analysis Techniques
Discovering Underlying Topics in the Newsgroups Dataset with Clustering and Topic Modeling
Recognizing Faces with Support Vector Machine
Machine Learning Best Practices
Categorizing Images of Clothing with Convolutional Neural Networks
Making Predictions with Sequences Using Recurrent Neural Networks
Advancing Language Understanding and Generation with the Transformer Models
Building an Image Search Engine Using CLIP: a Multimodal Approach
Making Decisions in Complex Environments with Reinforcement Learning
Other Books You May Enjoy
Index
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Master AI Agents: Build Powerful AI Agents and Generate Leads from Scratch
July 2025 | 642 pages
Learn About What Are AI Agents - For Beginners - The Essentials
Asking LLMs Like DeepSeek to Solve Problems for You
High-Level Overview of Our AI Agents and Email Personal Assistant
What Is N8N - Our Advanced Level AI Agent Building Tool
Building an Email Organizing AI Agent Automation
Authorizations for AI Agents with Businesses - Facebook and WhatsApp
Building Our AI Agent from Scratch - Memory and LLM Integration
Advanced - Adding Voice Integration and Custom HTTP Requests with WhatsApp AI
Integrating Email Actions for a WhatsApp AI Agent
Multi AI Agents and Sub-Workflows in N8N for Our Email AI Agent Assistant
An Overview and Live Example of the AI Agent Lead Generator Blueprint
Fundamental Data Flow for AI Agent Design - LLM Systems and APIs
Building the Lead Generating Chat AI Agent Model
Building the AI Agent Tool for Browser Searching and Database Updates
Linking Multiple Agentic Workflows Together to Build a Company of Agents
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C# 13 and .NET 9 – Modern Cross-Platform Development Fundamentals
November 2024 | 828 pages
Hello, C#! Welcome, .NET!
Speaking C#
Controlling Flow, Converting Types, and Handling Exceptions
Writing, Debugging, and Testing Functions
Building Your Own Types with Object-Oriented Programming
Implementing Interfaces and Inheriting Classes
Packaging and Distributing .NET Types
Working with Common .NET Types
Working with Files, Streams, and Serialization
Working with Data Using Entity Framework Core
Querying and Manipulating Data Using LINQ
Introducing Modern Web Development Using .NET
Building Websites Using ASP.NET Core
Building Interactive Web Components Using Blazor
Building and Consuming Web Services
Epilogue
Index
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LLM Design Patterns
May 2025 | 534 pages
Part 1: Introduction and Data Preparation
Chapter 1: Introduction to LLM Design Patterns
Chapter 2: Data Cleaning for LLM Training
Chapter 3: Data Augmentation
Chapter 4: Handling Large Datasets for LLM Training
Chapter 5: Data Versioning
Chapter 6: Dataset Annotation and Labeling
Part 2: Training and Optimization of Large Language Models
Chapter 7: Training Pipeline
Chapter 8: Hyperparameter Tuning
Chapter 9: Regularization
Chapter 10: Checkpointing and Recovery
Chapter 11: Fine-Tuning
Chapter 12: Model Pruning
Chapter 13: Quantization
Part 3: Evaluation and Interpretation of Large Language Models
Chapter 14: Evaluation Metrics
Chapter 15: Cross-Validation
Chapter 16: Interpretability
Chapter 17: Fairness and Bias Detection
Chapter 18: Adversarial Robustness
Chapter 19: Reinforcement Learning from Human Feedback
Part 4: Advanced Prompt Engineering Techniques
Chapter 20: Chain-of-Thought Prompting
Chapter 21: Tree-of-Thoughts Prompting
Chapter 22: Reasoning and Acting
Chapter 23: Reasoning WithOut Observation
Chapter 24: Reflection Techniques
Chapter 25: Automatic Multi-Step Reasoning and Tool Use
Part 5: Retrieval and Knowledge Integration in Large Language Models
Chapter 26: Retrieval-Augmented Generation
Chapter 27: Graph-Based RAG
Chapter 28: Advanced RAG
Chapter 29: Evaluating RAG Systems
Chapter 30: Agentic Patterns
Index
Other Books You May Enjoy
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Solutions Architect's Handbook
March 2024 | 582 pages
Solutions Architects in Organizations
Principles of Solution Architecture Design
Cloud Migration and Cloud Architecture Design
Solution Architecture Design Patterns
Cloud-Native Architecture Design Patterns
Performance Considerations
Security Considerations
Architectural Reliability Considerations
Operational Excellence Considerations
Cost Considerations
DevOps and Solution Architecture Framework
Data Engineering for Solution Architecture
Machine Learning Architecture
Generative AI Architecture
Rearchitecting Legacy Systems
Solution Architecture Document
Learning Soft Skills to Become a Better Solutions Architect
Other Books You May Enjoy
Index
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GitHub Copilot Complete Guide for Developers
July 2025 | 349 pages
Introduction to GitHub Copilot
GitHub Copilot Primer and Environment Setup
Day 1 – Foundations & Inline Code in GitHub Copilot
Day 2 – Conversational Workflows in GitHub Copilot
Day 3 – Project-Wide Intelligence in GitHub Copilot
Day 4 – Developer Collaboration in GitHub Copilot
Day 5 – Code Edits & Personalization in GitHub Copilot
Day 6 – Agents, Tools, & Extensions in GitHub Copilot
Conclusion
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