Books

Every secure communication begins with mathematics.Every modern encryption system relies on number theory.Every intelligent cyber defense increasingly depends on Artificial Intelligence.But what happens when these three worlds converge?In Cryptography, Number Theory, and AI Security, Anshuman Mishra takes readers on a journey from the mathematical foundations of encryption to the cutting-edge frontier of AI-powered cybersecurity.Explore prime numbers, RSA, elliptic curves, blockchain security, machine learning for threat detection, homomorphic encryption, federated learning, adversarial AI, and post-quantum cryptography.Discover how mathematics and machine intelligence work together to secure the digital world.

Prediction is only the beginning.Modern AI systems must explain their predictions, quantify uncertainty, scale to massive datasets, and operate reliably in real-world environments.How do Support Vector Regression models capture nonlinear patterns?How do Bayesian methods estimate uncertainty?How do Gaussian Processes make predictions with confidence intervals?How can complex AI models remain interpretable and trustworthy?In this advanced second volume, Anshuman Mishra explores the cutting-edge regression techniques that power intelligent prediction systems across machine learning, data science, healthcare, finance, robotics, and scientific research.Discover how modern Artificial Intelligence transforms data into reliable, explainable, and scalable predictions.

Lo que no te cuentan sobre construir el software que mueve un e-commerce en LATAM: facturación electrónica ante el SII, concurrencia con plata de por medio, marketplaces con sus gotchas no documentadas y multi-moneda sin descuadres de un peso. No es teoría ni un "hola mundo": son las decisiones, los bugs que costaron dinero y los patrones que vienen de operar un ERP multi-tenant real en producción.

Every intelligent prediction begins with a simple question:Can we model the relationship between data and outcomes?Regression is the foundation upon which modern predictive analytics, machine learning systems, and countless AI applications are built.From linear regression and regularization techniques to neural network regression, Gaussian processes, explainable AI, and real-world predictive systems, this book provides a complete roadmap for understanding how machines learn to predict.In Linear and Nonlinear Regression in Artificial Intelligence, Anshuman Mishra combines mathematical rigor, practical implementation, and real-world applications to help readers master one of the most powerful tools in Artificial Intelligence.Discover the mathematics behind prediction—and the science behind intelligent decision-making.

Artificial Intelligence does not learn in certainty.It learns through uncertainty, exploration, randomness, and adaptation.How does AlphaGo evaluate millions of possible moves?How do reinforcement learning agents discover optimal strategies?How do diffusion models generate realistic images?How do autonomous robots navigate uncertain environments?The answer lies in stochastic processes.In this advanced second volume, Anshuman Mishra explores the mathematical foundations behind reinforcement learning, probabilistic deep learning, robotics, generative AI, and emerging stochastic algorithms that are shaping the future of intelligent systems.Discover how randomness becomes learning—and how uncertainty becomes intelligence.

Artificial Intelligence is often described as learning from data.But beneath every learning algorithm lies something even more fundamental:Probability, randomness, and uncertainty.From Hidden Markov Models and stochastic gradient descent to Monte Carlo methods and reinforcement learning, modern AI systems depend on stochastic processes to make predictions, learn from experience, and adapt to changing environments.In Stochastic Processes in Artificial Intelligence, Anshuman Mishra provides a structured and accessible journey through the mathematical foundations that power intelligent systems.Discover how uncertainty becomes intelligence—and why stochastic thinking is essential for the future of Artificial Intelligence.

Every intelligent system faces a fundamental challenge:How do you find the best solution when there are millions—or even trillions—of possibilities?From A* search and heuristic optimization to neural architecture search, hyperparameter tuning, constraint satisfaction, and quantum optimization, modern AI depends on sophisticated strategies for navigating combinatorial search spaces.In this advanced second volume, Anshuman Mishra explores the powerful algorithms that enable intelligent systems to search smarter, optimize faster, and scale beyond brute force computation.Discover how combinatorial thinking drives machine learning, optimization, quantum AI, and the future of intelligent decision-making.The future of AI belongs to those who understand combinatorial complexity.

What if the monster didn’t escape into death… but was reborn to suffer as his victims once did? Shattered into animal forms and hunted by the souls he destroyed, Victor Kane’s eternal torment is only beginning. A brutal karmic nightmare where the apex predator becomes the ultimate prey.

Artificial Intelligence is not merely about data, learning, or neural networks—it is fundamentally about exploring vast spaces of possibilities.Every search algorithm, planning system, optimization framework, recommendation engine, and machine learning model faces a common challenge: navigating an enormous combinatorial universe of potential solutions.In Combinatorial Thinking in Artificial Intelligence, Anshuman Mishra reveals the mathematical foundations that drive modern AI systems. Through permutations, combinations, graph theory, probability, search strategies, and optimization techniques, readers learn how intelligent systems reason, search, and make decisions in complex environments.If you want to understand why AI algorithms work—not just how to implement them—this book provides the missing mathematical perspective.Discover the combinatorial engine behind intelligence.

Are you trapped in the "Paper-by-Paper" cycle of academic writing? The Research Production System™ provides the exact templates, AI-assisted workflows, and strategic frameworks required to transform sporadic research efforts into a structured, repeatable, and highly productive publication pipeline. Stop hoping for momentum and start engineering it today.

Advanced cybersecurity research based on multi-source data correlation across honeypots, IDS systems and network telemetry, analyzing unified attacker behavior and infrastructure patterns

Real-world network security research based on Suricata IDS data, analyzing malicious traffic, intrusion attempts and attack patterns observed at the network layer