User:Jayvanzyl/Books/Machine learning and data mining
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Machine learning and data mining
[edit]- Deep learning
- Machine learning
- Data mining
- Statistical classification
- Cluster analysis
- Regression analysis
- Anomaly detection
- Association rule learning
- Reinforcement learning
- Structured prediction
- Feature engineering
- Feature learning
- Online machine learning
- Semi-supervised learning
- Unsupervised learning
- Learning to rank
- Grammar induction
- Decision tree learning
- Supervised learning
- Ensemble learning
- Bootstrap aggregating
- Boosting (machine learning)
- Random forest
- K-nearest neighbors algorithm
- Linear regression
- Naive Bayes classifier
- Artificial neural network
- Logistic regression
- Perceptron
- Relevance vector machine
- Support vector machine
- Graphical model
- Local outlier factor
- Artificial intelligence
- Computational complexity theory
- Data collection
- Information extraction
- Data warehouse
- Data analysis
- Analytics
- Data dredging
- Computational statistics
- Hierarchical clustering
- K-means clustering
- Factor analysis
- Canonical correlation
- Linear discriminant analysis
- Non-negative matrix factorization
- Principal component analysis
- T-distributed stochastic neighbor embedding
- Meta learning
- Robot learning
- Developmental robotics
- Density estimation
- Dimensionality reduction
- Probability theory
- Generalized linear model
- Symbolic artificial intelligence
- Inductive logic programming
- Backpropagation
- Evolutionary algorithm
- Computational intelligence
- Fuzzy logic
- Evolutionary computation
- Swarm intelligence
- Artificial immune system
- Restricted Boltzmann machine
- Convolutional neural network
- Self-organizing map
- Multilayer perceptron
- Recurrent neural network
- Autoencoder
- Bias–variance tradeoff
- Empirical risk minimization
- Statistical learning theory
- Vapnik–Chervonenkis theory
- Probably approximately correct learning
- Deep belief network
- Feature extraction
- Linear map