User:Sebastian: Difference between revisions
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* [[Bit]] | * [[Bit]] | ||
* [[Byte]] | * [[Byte]] | ||
* [[Centroid linkage clustering]] | |||
* [[Classification]] | * [[Classification]] | ||
* [[Complete linkage clustering]] | |||
* [[Data mining]] | * [[Data mining]] | ||
* [[Evaluation metrics]] | * [[Evaluation metrics]] | ||
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* [[Machine learning algorithms]] | * [[Machine learning algorithms]] | ||
* [[Machine learning applications]] | * [[Machine learning applications]] | ||
* [[Mean linkage clustering]] | |||
* [[Multiple regression]] | * [[Multiple regression]] | ||
* [[Ordinal regression]] | * [[Ordinal regression]] | ||
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* [[Semi-supervised learning]] | * [[Semi-supervised learning]] | ||
* [[Simple regression]] ([[Simple linear regression]], [[Simple non-linear regression]]) | * [[Simple regression]] ([[Simple linear regression]], [[Simple non-linear regression]]) | ||
* [[Single linkage clustering]] | |||
* [[Unsupervised learning]] ([[clustering]], [[dimensionality reduction]], [[recommender system]]s, [[deep learning]], [[Density estimation]], [[Market basket analysis]]) | * [[Unsupervised learning]] ([[clustering]], [[dimensionality reduction]], [[recommender system]]s, [[deep learning]], [[Density estimation]], [[Market basket analysis]]) | ||
Revision as of 04:16, 9 May 2022
Vipul: "ok, so for ML wiki, I think you should pick some page or pages to write fully (i.e., long pages) and discuss with @Issa and me as you're doing it, so we can thnink through the right structure of the pages Vipul In parallel, you can continue the process of creating small, stub pages as you learn things Vipul Vipul Naik That's the T-shaped idea: do a few things deeply and then a lot of things (wide) and later you can deepen those other things."
All existing pages here[1]
Red links:
- Agglomerative clustering ([2])
- Anomaly detection
- Artificial intelligence
- Bayesian linear regression
- Bit
- Byte
- Centroid linkage clustering
- Classification
- Complete linkage clustering
- Data mining
- Evaluation metrics
- Expert system
- Hierarchical clustering
- Machine learning algorithms
- Machine learning applications
- Mean linkage clustering
- Multiple regression
- Ordinal regression
- Partitional clustering
- Poisson regression
- Reinforcement learning
- Semi-supervised learning
- Simple regression (Simple linear regression, Simple non-linear regression)
- Single linkage clustering
- Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning, Density estimation, Market basket analysis)
- Fast forest quantile regression
- Linear regression (expand)
- Polynomial regression
- Lasso regression
- Stepwise regression
- Ridge regression