AI & ML Handbook

AI & Machine Learning Handbook

Your Comprehensive Guide to Modern AI Algorithms

Powered by Solver360 - A Group of Powerful Solvers

29 Chapters • Complete Theory & Code Examples

Welcome to the Solver360 Handbook

This comprehensive handbook is your one-stop resource for understanding and implementing modern artificial intelligence and machine learning algorithms. Solver360 is a group of powerful solvers designed to tackle complex problems across mathematics, statistics, and AI. Each chapter provides in-depth theoretical explanations, mathematical foundations, practical implementations, and real-world applications.

What You'll Learn

Supervised Learning

Master regression, classification, and prediction algorithms including Linear/Logistic Regression, SVM, Decision Trees, and Neural Networks.

Deep Learning

Explore modern deep learning architectures including CNN, RNN, LSTM, Transformers, GANs, and Autoencoders.

Unsupervised Learning

Understand clustering, dimensionality reduction, and pattern discovery with K-Means, DBSCAN, and PCA.

Ensemble Methods

Learn powerful ensemble techniques like Random Forest, XGBoost, AdaBoost, and advanced boosting strategies.

Table of Contents

Fundamentals

Optimization Algorithms

Supervised Learning

Deep Learning

Ensemble Learning

Unsupervised Learning

Dimensionality Reduction

Data Preprocessing

Model Evaluation

Model Optimization

Time Series

Reinforcement Learning

Tools & Utilities

How to Use This Handbook

  1. Browse by Category: Use the sidebar to navigate through different topics organized by learning paradigm.
  2. Sequential Learning: Chapters are ordered from fundamental to advanced concepts. Reading sequentially is recommended for beginners.
  3. Search Functionality: Use the search bar to quickly find specific algorithms or concepts.
  4. Theory & Code Structure: Each chapter is divided into two main sections:
    • Theory & Concepts: Comprehensive explanations, mathematical formulations, and conceptual understanding
    • Code Implementation: Production-ready Python code examples with detailed implementations
  5. Interactive Learning: Navigate back to the main application to use interactive solvers and visualizations for each algorithm.

About This Handbook

All content in this handbook is generated from the actual theory and code sections used in Solver360 - a group of powerful solvers for mathematics, statistics, and AI. Each algorithm includes mathematical formulations using LaTeX, comprehensive explanations, practical examples, and production-ready code implementations in Python.

📧 Contact & Support

For questions, feedback, or support, please contact us at info@solver360.com

Solver360

A Group of Powerful Solvers for Mathematics, Statistics & AI

© 2026 Solver360. All rights reserved.

Free AI & ML Handbook • 29 Comprehensive Chapters • Theory & Code Examples