Machine Learning

ML concepts, algorithms, and practical guidance for building intelligent systems.

Foundations

• Supervised Learning
• Unsupervised Learning
• Reinforcement Learning
• Feature Engineering

Algorithms

• Linear Regression
• Decision Trees
• Neural Networks
• Clustering Algorithms

Deep Learning

• Convolutional Networks
• Recurrent Networks
• Transformers
• Embeddings
• Transfer Learning

MLOps

• MLOps
• Fine-Tuning
• Model Evaluation
• Overfitting
• Model Serving
• Experiment Tracking

Retrieval & Search

• Retrieval-Augmented Generation (RAG)
• Vector Databases

Applications

Entries coming soon

• Natural Language Processing
• Computer Vision
• Recommendation Systems
• Time Series Forecasting

Related Resources

• Fundamentals Domain - Underlying algorithms and mathematics
• DevOps Domain - Deployment and operations

Sources

Primary references for this domain:

• Hands-On Machine Learning - Aurelien Geron
• Deep Learning - Goodfellow, Bengio, Courville
• Pattern Recognition and Machine Learning - Christopher Bishop