AI Tutorials

Guide from beginner to advanced. Learn machine learning, neural networks, embeddings, transformers, and RAG.

Total Tutorials

Levels

Beginner Level

Foundations of machine learning and neural networks.

Introduction to Machine Learning

Learn what machine learning is and how it differs from traditional programming. Covers supervised, unsupervised, and reinforcement learning with Python and SQL examples.

NeuronDB Team

2/24/2025

Beginner

Data Preparation and Feature Engineering

Learn data collection, cleaning, feature selection, and transformation. Learn to handle missing values, outliers, normalization, and standardization with practical examples.

NeuronDB Team

2/24/2025

Beginner

Linear Models: Regression and Classification

Understand linear regression and logistic regression. Learn cost functions, gradient descent, and model evaluation metrics with Python and SQL implementations.

NeuronDB Team

2/24/2025

Beginner

Neural Networks: From Perceptrons to Deep Learning

Build neural networks from scratch. Learn perceptrons, multi-layer networks, activation functions, and forward propagation with NumPy and SQL storage examples.

NeuronDB Team

2/24/2025

Beginner

Training Neural Networks

Learn loss functions, backpropagation, optimizers, and learning rates. Implement training loops in Python and log metrics in SQL databases.

NeuronDB Team

2/24/2025

Beginner

Overfitting and Regularization

Understand bias-variance tradeoff, overfitting detection, and regularization techniques. Learn L1, L2, dropout, and cross-validation with examples.

NeuronDB Team

2/24/2025

Intermediate Level

Practical applications with embeddings, transformers, and search.

Intermediate

Embeddings: Representing Data as Vectors

Learn word embeddings, sentence embeddings, and document embeddings. Understand embedding properties, similarity, and arithmetic with practical examples.

NeuronDB Team

2/24/2025

Intermediate

Transformers: Architecture and Self-Attention

Learn the transformer architecture and self-attention mechanism. Learn multi-head attention, encoder-decoder structures, and positional encoding.

NeuronDB Team

2/24/2025

Intermediate

Large Language Models: How LLMs Work

Understand pre-training, fine-tuning, tokenization, and model architectures. Learn GPT, BERT, and T5 with inference and generation examples.

NeuronDB Team

2/24/2025

Intermediate

Vector Search: Similarity and Distance Metrics

Learn vector similarity concepts and distance metrics. Learn cosine, Euclidean, and Manhattan distances with indexing strategies and SQL examples.

NeuronDB Team

2/24/2025

Intermediate

Semantic Search: Finding Meaning in Text

Build semantic search systems with document chunking, query processing, and ranking. Learn keyword vs semantic search with implementations.

NeuronDB Team

2/24/2025

Intermediate

RAG Fundamentals: Retrieval-Augmented Generation Basics

Learn RAG architecture, document processing, retrieval strategies, and context building. Build RAG systems with Python and SQL examples.

NeuronDB Team

2/24/2025

Advanced Level

Deep dive into advanced architectures and production deployment.

Advanced

Advanced RAG: Hybrid Search and Reranking

Learn hybrid search combining semantic and keyword search. Learn reranking strategies, multi-vector approaches, and temporal search with SQL examples.

NeuronDB Team

2/24/2025

Advanced

Prompt Engineering: Techniques and Best Practices

Learn prompt design principles, few-shot learning, chain-of-thought prompting, and optimization. Build prompt template systems with examples.

NeuronDB Team

2/24/2025

Advanced

Model Evaluation: Metrics and Testing

Classification and regression metrics. Learn embedding quality metrics, A/B testing, and evaluation suites with SQL storage.

NeuronDB Team

2/24/2025

Advanced

Fine-tuning: Adapting Models to Your Data

Understand transfer learning and fine-tuning strategies. Learn dataset preparation, training procedures, and evaluation with transformer examples.

NeuronDB Team

2/24/2025

Advanced

Production Deployment: Scaling and Optimization

Learn model serving architectures, batch vs real-time inference, performance optimization, caching, and monitoring with deployment examples.

NeuronDB Team

2/24/2025

Advanced

Advanced Architectures: Multi-vector and Temporal Search

Learn multi-vector embeddings, temporal search patterns, ensemble methods, and advanced indexing with complex architecture implementations.

NeuronDB Team

2/24/2025