Machine Learning Reference
Quickly find what you need for your ML-project
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Quick info
This is a reference on applied machine learning for daily use. The topics range from math fundamentals to complex machine learning models and explanation methods. The focus lies on concise explanations and practical code snippets.
As an ML engineer or data scientist, you can …
- Use the search-field and quickly find solutions for your tasks and copy the code snippet into your project.
- Refresh you knowledge about a topic and find references for further reading.
The currently incomplete sections are marked in grey.
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- Write/adapt a chapter, section, paragraph?
- Create figures?
- Or proofread new chapters?
Please write an email to ml_reference[ät]icloud.com
Your benefits: Good karma, “While we teach, we learn”, Being listed as an author on this page.
You found errors or unclear explanations? You have a good idea? Please file an issue under: github.com/MoritzGuck/Machine-Learning-Reference or write an email to ml_reference[ät]icloud.com.
- Machine Learning Glossary: An online book with more details on underlying mechanisms and a large chapter on fundamentals in maths and neural networks.
- R Cookbook: A comprehensive online book on R and specific problems.
- Google Machine Learning Glossary: Glossary with brief explanations on fundamental machine learning topics.
- Distill: Beautiful and easy to understand visualizations and articles on machine learning algorithms.