This repository introduces the basics of machine learning algorithms for preprocessing, regression and classification tasks covering the basic theory and common concepts and techniques involved in Machine Learning. This repository is for beginners who are interested in machine learning.
InfiniteBoost Code for a paper InfiniteBoost: building infinite ensembles with gradient descent (arXiv:1706.01109). A. Rogozhnikov, T. Likhomanenko De
Feature-Engineering Required for a machine learning pipeline data preprocessing and variable engineering script needs to be prepared. When the dataset
TensorHive is an open source tool for managing computing resources used by multiple users across distributed hosts. It focuses on granting
Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson curriculum all about Machine Learning
XGBoost-Ray is a distributed backend for XGBoost, built on top of distributed computing framework Ray.
MLOps template with examples for Data pipelines, ML workflow management, API development and Monitoring.
ClearML - Auto-Magical Suite of tools to streamline your ML workflow Experiment Manager, MLOps and Data-Management ClearML Formerly known as Allegro T
AutoTabular AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just
LRM-Squannacook Input data for generating stochastic streamflows are observed and simulated timeseries of streamflow. their format needs to be CSV wit
Pandas DataFrames and Series as Interactive Tables in Jupyter Star Turn pandas DataFrames and Series into interactive datatables in both your notebook
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learn
DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning. DirectML provides GPU acceleration for common machine learning tasks across a broad range of supported ha
MLOps The MLOps is the process of continuous integration and continuous delivery of Machine Learning artifacts as a software product, keeping it insid
Prince is a library for doing factor analysis. This includes a variety of methods including principal component analysis (PCA) and correspondence anal
A corona statistics and information telegram bot.
Simple but maybe too simple config management through python data classes. We use it for machine learning.
Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a
SmartSim Example Zoo This repository contains CrayLabs and user contibuted examples of using SmartSim for various simulation and machine learning appl
This project shows steps to build an end to end MLOps architecture that covers data prep, model training, realtime and batch inference, build model registry, track lineage of artifacts and model drif
Medical Data for Machine Learning This is a curated list of medical data for machine learning. This list is provided for informational purposes only,
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