User:Sebastian

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
• Autoencoder
• Artificial intelligence
• Bayesian linear regression
• Bit
• Byte
• Centroid linkage clustering
• Classification
• Complete linkage clustering
• Data mining
• Dendogram
• Dimensionality reduction ([3])
• Evaluation metrics
• Expert system
• Fast forest quantile regression
• Feature extraction ([4])
• Feature selection ([5])
• Hierarchical clustering
• Lasso regression
• Linear regression (expand)
• Machine learning algorithms
• Machine learning applications
• Manifold hypothesis
• Mean linkage clustering
• Multiple regression
• Ordinal regression
• Partitional clustering
• Poisson regression
• Polynomial regression
• Reinforcement learning
• Semi-supervised learning
• Simple regression (Simple linear regression, Simple non-linear regression)
• Single linkage clustering
• Stepwise regression
• Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning, Density estimation, Market basket analysis)

• Ridge regression

• Neural network regression
• Decision forest regression
• Regression model
• Boosted decision tree regression
• Python
• NumPy
• scikit-learn
• Pytorch
• SciPy
• matplotlib
• pandas
• Dataset
• Standard deviation
• TensorFlow
• Training accuracy
• Out-of-sample accuracy
• Procgen Benchmark
• Optimization

• Silhouette score ([6])
• Soft computing

• K-nearest neighbor

• NumPy [7]
• SciPy [8]
• matplotlib [9]
• pandas [10]
• scikit-learn [11]
• Clustering [12]