Analytics & Machine Learning R Sidekick
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Updated
May 27, 2024 - R
Analytics & Machine Learning R Sidekick
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
R package for automation of machine learning, forecasting, model evaluation, and model interpretation
Sparkling Water provides H2O functionality inside Spark cluster
This project focuses on analyzing diabetes-related data and building predictive models using KNIME. The main objectives of the project include:
Tutorials and training material for the H2O Machine Learning Platform
Comparison tools
This project is a classification problem with a response variable to classify handwritten images as the numbers, 'one', 'seven' or 'eight. This is a classification problem using the Cross Entropy loss function, the 'tanh' activation function using h2o deeplearning as well as Trees.
autoEnsemble : An AutoML Algorithm for Building Homogeneous and Heterogeneous Stacked Ensemble Models by Searching for Diverse Base-Learners
A Python Data Project using H2O and Decision Trees to predict the 2024 Premier League Table based on the previous 30 years.
A curated list of gradient boosting research papers with implementations.
Production ready templates for deploying Driverless AI (DAI) scorers. https://h2oai.github.io/dai-deployment-templates/
DayF (Decision at your Fingertips) is an AutoML opensource project
Forecasting with H2O AutoML. Use the H2O Automatic Machine Learning algorithm as a backend for Modeltime Time Series Forecasting.
ForestFlow is a policy-driven Machine Learning Model Server. It is an LF AI Foundation incubation project.
This project contains examples which demonstrate how to deploy analytic models to mission-critical, scalable production environments leveraging Apache Kafka and its Streams API. Models are built with Python, H2O, TensorFlow, Keras, DeepLearning4 and other technologies.
An ebuild repository for Apache Spark, H2O.ai and Kotlin on Gentoo (Development fork - please check main repo first)
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