The Grand AI Handbook

AI Handbooks

Browse our collection of comprehensive AI handbooks covering various domains and technologies.

Generative AI

Generative AI

Systems that create text, images, music, and code through AI techniques.

Transformers Diffusion GANs
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Core AI Fields

Foundation Models

Large-scale AI models trained on diverse data for many tasks.

Transfer Learning Fine-tuning Scaling Laws
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Computer Vision

Computer Vision

How AI systems process and understand visual information.

CNNs ViT YOLO
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Reinforcement Learning

Reinforcement Learning

How AI agents learn through interaction with environments.

DQN PPO SAC
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Core AI Fields

Machine Learning

Algorithms that enable computers to learn from data.

Supervised Unsupervised Semi-supervised
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Core AI Fields

Deep Learning

Neural network architectures that power modern AI systems.

Neural Networks Backprop Activation Functions
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NLP

NLP

How AI systems understand and generate human language.

BERT GPT T5
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Core AI Fields

Large Language Models

Neural networks trained to understand and generate language.

Transformers Attention RLHF
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Core AI Fields

MLOps

Deploying and managing ML models in production.

Deployment Monitoring Versioning
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AI Domains

Explainable AI (XAI)

Understanding and interpreting AI decision-making.

LIME SHAP Feature Importance
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AI Domains

Federated Learning

Training models across decentralized devices while preserving privacy.

Privacy Distributed Encryption
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AI Domains

Multimodal AI

Systems that process and connect multiple types of data inputs.

Vision-Language CLIP Multimodal Fusion
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AI Domains

Recommender Systems

AI systems that suggest relevant items to users.

Collaborative Filtering Content-Based Matrix Factorization
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AI Domains

Robotics & AI

How AI systems power and control physical robots.

Control Perception Manipulation
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AI Domains

Self-Driving Cars

AI technologies enabling autonomous vehicle navigation.

Computer Vision Decision Making Path Planning
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AI Domains

Audio AI

AI systems for speech recognition, audio generation and processing.

Speech Recognition Audio Synthesis Acoustic Models
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Specialized AI Techniques

Bayesian Machine Learning

Probabilistic approaches to ML using Bayesian inference.

Probability Uncertainty MCMC
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Specialized AI Techniques

Efficient AI & Optimization

Techniques to make AI systems faster and more resource-efficient.

Quantization Pruning Knowledge Distillation
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Specialized AI Techniques

Graph Neural Networks

Neural networks designed to work with graph-structured data.

GCN Graph Embeddings Message Passing
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Specialized AI Techniques

Representation Learning

Methods for learning useful data representations without supervision.

Embeddings Feature Learning Latent Space
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Specialized AI Techniques

Self-Supervised Learning

Learning from unlabeled data using automatically generated supervision.

Contrastive Learning Masking SimCLR
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Specialized AI Techniques

Time Series Forecasting

AI methods for predicting future values based on past observations.

ARIMA Prophet LSTM
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Applied AI & Ethics

AI Ethics & Fairness

Ensuring AI systems are fair, accountable, and transparent.

Bias Governance Transparency
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Applied AI & Ethics

AI for Art & Aesthetics

How AI systems create and evaluate visual art and design.

Creativity Style Transfer Stable Diffusion
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Applied AI & Ethics

AI for Edge & IoT

Deploying AI on resource-constrained devices and IoT networks.

TinyML Embedded Energy Efficiency
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Applied AI & Ethics

AI in Finance

Applications of AI in financial markets and institutions.

Trading Risk Fraud Detection
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Applied AI & Ethics

AI in Healthcare

How AI is transforming medical diagnosis, treatment, and research.

Medical Imaging Diagnostics Genomics
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Uncategorized

AI Agents

Exploring autonomous AI systems that can perceive, decide, and act independently.

Reinforcement Learning Multi-agent Systems Robotics
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Uncategorized

Prompt Engineering

Mastering the art and science of crafting effective prompts for language models.

Chain-of-Thought ReAct LLM Judge
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Uncategorized

Quantum ML

The intersection of quantum computing and machine learning algorithms.

Quantum Circuits Hybrid Algorithms Quantum Advantage
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How to Use These Handbooks

1️⃣

Start with Fundamentals

Begin with the introductory sections to build a solid foundation.

2️⃣

Explore Techniques

Dive into specific techniques and architectures that interest you.

3️⃣

Try Applications

Apply your knowledge to practical use cases and projects.

Coming Soon:

  • AI Agents Handbook - Building autonomous systems for complex tasks
  • Prompt Engineering Handbook - Master the art of effective AI communication
  • Quantum ML Handbook - Exploring computational advantages of quantum systems

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