2 repository-uri
Awesome GitHub RepositoriesRegression Implementations
Implementations of regression methods including linear basis function models and Gaussian processes from the PRML textbook.
Distinct from Linear Regression Implementations: Distinct from Linear Regression Implementations: covers a broader range of regression methods including Gaussian processes, not just linear regression.
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Awesome Regression Implementations GitHub Repositories
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- prml/prmlt
PRML/PRMLT
6,207Vezi pe GitHubPRMLT provides self-contained MATLAB implementations of every algorithm from the Pattern Recognition and Machine Learning textbook by Christopher Bishop. The code reproduces the book's exact formulas and notation, making each implementation directly traceable to the source material for educational verification and study. The implementations cover the full range of core machine learning methods from the textbook, including classification, clustering, regression, density estimation, and neural network algorithms. Each module is self-contained with heavy comments, and the code uses compact, vect
Implements regression methods including linear basis function models and Gaussian processes from the PRML textbook.
MATLAB - binroot/tensorflow-book
BinRoot/TensorFlow-Book
4,431Vezi pe GitHubThis project is a collection of TensorFlow machine learning examples providing reference implementations for various neural network paradigms. It covers supervised, unsupervised, reinforcement, and sequential learning models. The repository includes implementations for convolutional neural networks focused on image classification and ranking, as well as recurrent neural networks for time-series forecasting and sequence-to-sequence translation. It further provides examples of reinforcement learning agents trained via reward optimization and unsupervised learning techniques such as autoencoders
Implements a range of regression methods to predict continuous values by fitting linear and non-linear relationships.
Jupyter Notebookautoencoderbookclassification
