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- What is this section?
- Foundations
- Machine Learning
- Machine Learning
- Python (Helsinki MOOC 2024)
- Python
- Python Helsinki: 1
- Python Helsinki: 2
- Python Helsinki: 3
- Python Helsinki: 4
- Python Helsinki: 5
- Python Helsinki: 6
- Python Helsinki: 7
- Python Helsinki: 8
- Python Helsinki: 9
- Python Helsinki: 10
- Python Helsinki: 11
- Python Helsinki: 12
- Python Helsinki: 13
- Python Helsinki: 14
- Labs
- Foundations: Labs
- Resources
- Foundations: Resources
Data
- What is this section?
- Big Data
- Labs
- Data: Labs
- Resources
- Data: Resources
Classic ML
- What is Classic ML?
- Algorithms: Introduction
- Algorithm Types
- Algorithms: Linear regression
- Algorithms: Logistic regression
- Algorithms: Naïve Bayes
- Algorithms: Support Vector Machines
- Algorithms: Decision tree
- Algorithms: K-Nearest neighbor
- Algorithms: Random forest
- Algorithms: Gradient boosting
- Algorithms: K-Means
- Labs
- Classic ML: Labs
- Resources
- Classic ML: Resources
Evaluation
- What is this section?
- Model evaluation
- Labs
- Model evaluation: Labs
- Resources
- Model evaluation: Resources
Deep Learning
- ANN
- ANN: Table of Contents
- ANN: Introduction
- ANN: Mathematical Model
- ANN: model and demos
- Introduction to Deep Learning
- Deep Learning
- Labs
- Deep Learning: Labs
- Resources
- Deep Learning: Resources
LLMs
- Generative AI
- Generative AI
- LLMs
- Large Language Models
- GPT
- Transformers
- The Transformer
- Labs
- LLMs and Transformers: Labs
- Resources
- LLMs and Transformers: Resources
RAG & Agents
- What is this section?
- RAG and agents
- RAG
- RAG
- Labs
- RAG and agents: Labs
- Resources
- RAG and agents: Resources
AI for Devs
- What is this section?
- AI for developers
- Labs
- AI for developers: Labs
- Resources
- AI for developers: Resources
MLOps
- What is this section?
- MLOps
- Labs
- MLOps: Labs
- Resources
- MLOps: Resources
Training
- About Training
- Training
- Labs
- Training: Labs
- Resources
- Training: Resources

Resources
Classic ML: Resources

Classic ML
What is Classic ML?
- Algorithms: Introduction
Algorithm Types
Labs
- Classic ML: Labs
Resources
- Classic ML: Resources

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Resources for this section

Resources
Classic ML: Resources

Classic ML: Resources

Resources for this section

A dedicated reading list for classic algorithms is not written yet. Start from the algorithms overview and the site-wide Resources list.

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