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Usage | Algorithm |
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- Trend Prediction
- Curve fitting
- Relationship between variables
| Linear Regression | - classify data in 2 Categories
- finding the best way to split a dataset
| Logistic Regression | - classifying data into multiple categories
| Softmax Regression | - reveal hidden causes of observations
- finding the most likely cause for a series of outcomes
| Hidden Markov | - classify data into a fixed number of categories
- automatically partition data into separate classes
| K-Means Clustering | - cluster data into arbitrary categories
- visualize high-dimensional data into a lower-dimensional embedding
| Self-Organizing Map | - reduce dimensionality of data
- learn latent variables responsible for high-dimensional data
| Autoencoder | - plan actions in an environment using neural networks (reinforcement learning)
| Q-policy neural network | - classify data using supervised neural networks
| Perceptron | - classify real-world images using supervised neuronal networks
| Convolutional Neuronal Network | - produce patterns that match observations using neural networks
| Recurrent Neuronal Network | - predicting natural language responses to natural language queries
| Seq2Seq | - rank items by learning their utility
| Ranking |
- TensorFlowSharp. TensorFlow API for .NET languages. In: GitHub. Miguel de Icaza, abgerufen am 14. Mai 2017 (englisch).
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