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Easy-to-use Federated Learning Platform.
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A fast Evolution Strategy implementation in Python.
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High-level wrapper built on the top of Pytorch which supports vision, text, tabular data and collaborative filtering.
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A collection of functions for mathematical and statistical computing, macine learning, etc., wrapping several JVM libraries.
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Large scale Gaussian Mixture Models.
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If this is your first time building with Generative AI models, check out our course, which includes 21 lessons on building with GenAI.
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Course content and resources for the AIAIART course.
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Generalized linear models in Julia.
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Julia wrapper for fitting Lasso/ElasticNet GLM models using glmnet.
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Deep Neural Networks for Golang (powered by MXNet).
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An offline recommender system backend based on collaborative filtering written in Go.
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ML engine that supports distributed learning on Hadoop, Spark or your laptop via APIs in R, Python, Scala, REST/JSON.
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A hands-on course to train and deploy a serverless API that predicts crypto prices.
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Python materials for the online course on diffusion models by @huggingface.
IPython notebooks from Data School's video tutorials on scikit-learn.
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A Java port of SciPy's signal processing module, offering filters, transformations, and other scientific computing utilities.
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Clojure wrapper for deeplearning4j with some added syntactic sugar.
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Run Keras models in the browser, with GPU support provided by WebGL 2.
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Kernel density estimators for Julia.
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Simple API for Neural Network. Better for image processing with CPU/GPU + Transfer Learning.
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JavaScript implementation of the k nearest neighbors algorithm for supervised learning.
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A pure Go implementation of the prediction part of GBRTs, including XGBoost and LightGBM.
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A generic approach that allows to mimic most factorization models by feature engineering.