#Tech_book
"ChatGPT for Cybersecurity Cookbook:
Learn practical generative AI recipes to supercharge your cybersecurity skills", 2024.

#MLSecOps
#Tech_book
"The Developer’s Playbook for Large Language Model Security: Building Secure AI Applications", 2024.

#Tech_book
"Python Debugging for AI, Machine Learning, and Cloud Computing: A Pattern-Oriented Approach", 2024.

#MLSecOps
#Tech_book
"Large Language Models in Cybersecurity:
Threats, Exposure and Mitigation", 2024.

#DevOps
#Tech_book
#Sec_code_review
"Clean Code Principles and Patterns:
A Software Practitioner’s Handbook",
2nd Edition, 2024.

#Tech_book
"PowerShell for Penetration Testing:
Explore the capabilities of PowerShell for pentesters across multiple platforms", 2024.

#Tech_book
"Generative AI Apps with LangChain and Python: A Project-Based Approach to Building Real World LLM Apps", 2024.

#CogSec
#Tech_book
"Ultimate Deepfake Detection Using Python:
Master Deep Learning Techniques like CNNs, GANs, and Transformers to Detect Deepfakes in Images, Audio, and Videos Using Python", 2024.

]-> Repo: https://github.com/ava-orange-education/Ultimate-Deepfake-Detection-Using-Python

#Tech_book
"Red Teaming AI:
Attacking & Defending Intelligent Systems", 2025.

// While other resources may list vulnerabilities, our focus is on how to think like an attacker attacking intelligent systems, how to proactively identify these unique patterns, and how to build more resilient systems based on this understanding

#MLSecOps
#Tech_book
"Adversarial AI Attacks, Mitigations, and Defense Strategies: A cybersecurity professional’s guide to AI attacks, threat modeling, and securing AI with MLSecOps', 2024.

// The book is for cybersecurity professionals, such as security architects, analysts, engineers, ethical hackers, pentesters, and incident responders, but also developers and engineers designing, building, and assuring AI systems

#AIOps
#MLSecOps
#Tech_book
"Machine Learning Systems:
Principles and Practices of Engineering Artificially Intelligent Systems",
School of Engineering and Applied Sciences Harvard University, Nov. 4, 2025.

// This book bridges the gap between theoretical foundations and practical engineering, emphasizing the systems perspective required to build effective AI solutions. Unlike resources that focus primarily on algorithms and model architectures, this book highlights the broader context in which ML systems operate, including data engineering, model optimization, hardware-aware training, and inference acceleration

#Tech_book
"Artificial Intelligence for Cybersecurity:
Develop AI approaches to solve cybersecurity problems in your organization", 2024.

// This book is for cybersecurity or general IT professionals or students who are interested in AI technologies and how they can be applied in the cybersecurity context

#AIOps
#Tech_book
"Building Agentic AI Systems:
Create intelligent, autonomous AI agents that can reason, plan, and adapt", First Edition, 2025.
]-> Code Repository

// With the rise of Generative AI and agentic systems, we are witnessing a transformative moment, one where artificial agents can reflect upon their experiences, strategize effectively, and collaborate seamlessly. This book arrives precisely at this pivotal juncture, offering a comprehensive exploration of this emerging and impactful field

#AIOps
#Tech_book
"Agentic Design Patterns: A Hands-On Guide to Building Intelligent Systems", Oct. 2025.

// A comprehensive guide presenting 21 design patterns for building AI agents, using frameworks like LangChain, Crew AI, and Google ADK to create autonomous intelligent systems

#MLSecOps
#Tech_book
"Introduction to Machine Learning with Security:
Theory and Practice Using Python in the Cloud",
Second Edition, 2025.

// This book provides an introduction to machine learning, security and cloud computing, from a conceptual level, along with their usage with underlying infrastructure

#MLSecOps
#Tech_book
"Generative AI with LangChain:
Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph",
2nd Edition, 2025.

// Go beyond foundational LangChain documentation with detailed coverage of LangGraph interfaces, design patterns for building AI agents, and scalable architectures used in production - ideal for Python developers building GenAI applications

#MLSecOps
#Tech_book
"Machine Learning for High-Risk Applications:
Approaches to Responsible AI", 2023.

// This book describes approaches to responsible AI - a holistic framework for improving AI/ML technology, business processes, and cultural competencies that builds on best practices in risk management, cybersecurity, data privacy, and applied social science

#AIOps
#Tech_book
"Agentic AI in Enterprise: Harnessing Agentic AI for Business Transformation", 2025.

// This book delves into the transformative power of Enterprise Agentic AI, tracing its evolution from basic automation to intelligent agents capable of contextual reasoning, memory retention, and autonomous decision-making