High-level wrapper built on the top of Pytorch which supports vision, text, tabular data and collaborative filtering.
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Large scale Gaussian Mixture Models.
If this is your first time building with Generative AI models, check out our course, which includes 21 lessons on building with GenAI.
Course content and resources for the AIAIART course.
Generalized linear models in Julia.
Julia wrapper for fitting Lasso/ElasticNet GLM models using glmnet.
Deep Neural Networks for Golang (powered by MXNet).
An offline recommender system backend based on collaborative filtering written in Go.
A hands-on course to train and deploy a serverless API that predicts crypto prices.
Python materials for the online course on diffusion models by @huggingface.
A Java port of SciPy's signal processing module, offering filters, transformations, and other scientific computing utilities.
Clojure wrapper for deeplearning4j with some added syntactic sugar.
Run Keras models in the browser, with GPU support provided by WebGL 2.
Kernel density estimators for Julia.
A pure Go implementation of the prediction part of GBRTs, including XGBoost and LightGBM.
A generic approach that allows to mimic most factorization models by feature engineering.
A minimal, educational, Pythonic implementation of autograd (~100 loc).
A Repository Containing Classification, Clustering, Regression, Recommender Notebooks with illustration to make them.
Lightweight ML utility for automated training, evaluation, and prediction with CLI and Python API support.
Multidimensional cluster generation in MATLAB/Octave.
It implemented multi-perceptrons neural network (ニューラルネットワーク) based on Back Propagation Neural Networks (BPN) and designed unlimited-hidden-layers.
Methods for dimensionality reduction.
A library of shared system prompts for creating customized educational GPT agents.