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The ML / AI track.

Machine learning, deep learning, neural networks, scikit-learn, TensorFlow and PyTorch. Built as a curriculum — 26 chapters, recommended spine if you're new, side-quests when you're ready.

⏱ ~24h 2m total 39 beginner · 98 intermediate · 69 advanced 📚 206 topics

You'll cover: ML Basics, Math for ML, Algorithms — then go deeper.

Start here: Introduction to Machine Learning → Supervised vs Unsupervised Learning → ML Workflow — Data to Deployment →

Continue from Introduction to Machine Learning → Complete ML / AI guide

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CURRICULUM

26 chapters · 206 topics

ML Basics

SPINEBeginner

26 topics · ~3h 2m · 0/26 read

Introduction to Machine Learning Supervised vs Unsupervised Learning ML Workflow — Data to Deployment Overfitting and Underfitting Train Test Split and Cross Validation+21 more

Math for ML

SPINEIntermediate

7 topics · ~49m · 0/7 read

Linear Algebra for Machine Learning Calculus for Machine Learning Probability for Machine Learning Bayes' Theorem in Machine Learning Eigenvalues and Eigenvectors Explained+2 more

Algorithms

SPINEIntermediate

21 topics · ~2h 27m · 0/21 read

Linear Regression Logistic Regression Decision Trees Random Forest Algorithm Explained Support Vector Machine+16 more

Deep Learning

SPINEAdvanced

23 topics · ~2h 41m · 0/23 read

What is a Neural Network? Explained Simply Activation Functions in Neural Networks Backpropagation Explained Convolutional Neural Networks Recurrent Neural Networks and LSTM+18 more

Reinforcement Learning

SPINEAdvanced

12 topics · ~1h 24m · 0/12 read

Markov Decision Processes (MDPs)Q-Learning Explained Temporal Difference Learning (SARSA vs Q-Learning)Deep Q-Networks (DQN)Policy Gradient Methods+7 more

From Scratch

SPINEAdvanced

4 topics · ~28m · 0/4 read

Neural Network from Scratch in NumPy Build an Autograd Engine from Scratch Build GPT from Scratch Build a BPE Tokenizer from Scratch

Tools

SPINEIntermediate

14 topics · ~1h 38m · 0/14 read

scikit-learn Tutorial TensorFlow Basics PyTorch Basics Keras for Deep Learning Jupyter Notebook Guide+9 more

NLP

SPINEIntermediate

11 topics · ~1h 17m · 0/11 read

Natural Language Processing (NLP) Explained Text Preprocessing in NLP Word Embeddings — Word2Vec GloVe Sentiment Analysis Named Entity Recognition+6 more

MLOps

SPINEAdvanced

14 topics · ~1h 38m · 0/14 read

Introduction to MLOps Model Deployment with Flask ML Model Evaluation Metrics A/B Testing in ML Docker for ML Models+9 more

TensorFlow & Keras

SPINEIntermediate

11 topics · ~1h 17m · 0/11 read

Introduction to TensorFlow TensorFlow vs PyTorch — Which to Learn First Introduction to Keras Building Your First Neural Network with Keras Keras Sequential vs Functional API+6 more

Scikit-Learn

SPINEBeginner

9 topics · ~1h 3m · 0/9 read

Introduction to Scikit-Learn Scikit-Learn Pipeline Explained Train Test Split and Cross Validation in Scikit-Learn Linear Regression with Scikit-Learn Classification with Scikit-Learn+4 more

PyTorch

SPINEIntermediate

7 topics · ~49m · 0/7 read

Introduction to PyTorch PyTorch Tensors Explained Building a Neural Network in PyTorch Autograd and Backpropagation in PyTorch Training Loop in PyTorch Explained+2 more

SPINEIntermediate

3 topics · ~21m · 0/3 read

Introduction to Neural Networks Introduction to NLP Random Forest

Prompt Engineering

SPINEBeginner

5 topics · ~35m · 0/5 read

Prompt Engineering Chain of Thought Prompting Few-Shot vs Zero-Shot Prompting Role-Based System Prompts for LLMs Prompt Templates and Best Practices

LLM Basics

SPINEAdvanced

8 topics · ~56m · 0/8 read

LLM Context Window Explained Mixture of Experts (MoE) in LLMs LLM Tokenization Explained RLHF — Reinforcement Learning from Human Feedback LLM Fine-Tuning Guide+3 more

LLM APIs

Intermediate

3 topics · ~21m · 0/3 read

OpenAI API Python Guide LLM Function Calling Explained Structured Outputs with LLMs

RAG

Intermediate

5 topics · ~35m · 0/5 read

Vector Databases Explained RAG Pipeline Explained RAG Chunking Strategies Embeddings and Semantic Search Advanced RAG Techniques

AI Agents

Intermediate

5 topics · ~35m · 0/5 read

AI Agents Explained ReAct Agent Pattern Agent Memory Types Tool Use in AI Agents Model Context Protocol (MCP) Explained

Agent Frameworks

Intermediate

4 topics · ~28m · 0/4 read

LangGraph Tutorial CrewAI Multi-Agent Tutorial Agent Orchestration Patterns Agentic Planning Strategies

Multi-Agent

Advanced

3 topics · ~21m · 0/3 read

Multi-Agent Systems Explained Agent Communication Patterns A2A Protocol for AI Agents

Context Engineering

Intermediate

4 topics · ~28m · 0/4 read

Context Engineering for LLMs Token Budgeting for LLMs LLM Memory Management Context Compression Techniques

Observability

Intermediate

3 topics · ~21m · 0/3 read

LLM Observability Tools LLM Evaluation Frameworks LLM Latency Optimization

Local Models

Beginner

1 topics · ~7m · 0/1 read

Ollama Local LLM Guide

Agents

Intermediate

1 topics · ~7m · 0/1 read

MCP Ollama Bridge for Local Agents

LLMOps

Intermediate

1 topics · ~7m · 0/1 read

Prompt Caching in Production LLMs

Safety

Intermediate

1 topics · ~7m · 0/1 read

LLM Guardrails in Production