A Tools that help Data Scientists and ML engineers train and deploy ML models.

Overview

Domino Research

This repo contains projects under active development by the Domino R&D team. We build tools that help Data Scientists and ML engineers train and deploy ML models.

Active Projects

Here’s what we’re working on:

  • 🌉 Bridge - deploy directly from your registry, turning it into a declarative source of truth for your model hosting.

  • 🛂 Checkpoint - adds 'Pull Requests' to your registry to create a better process for promoting models to production.

  • 🎇 Flare - monitor models and get alerts without capturing, storing or processing production inference data.

Owner
Domino Data Lab
Domino Data Lab
A collection of interactive machine-learning experiments: 🏋️models training + 🎨models demo

🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo

Oleksii Trekhleb 1.4k Jan 06, 2023
Banpei is a Python package of the anomaly detection.

Banpei Banpei is a Python package of the anomaly detection. Anomaly detection is a technique used to identify unusual patterns that do not conform to

Hirofumi Tsuruta 282 Jan 03, 2023
This repository contains the code to predict house price using Linear Regression Method

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A naive Bayes model for cancer classification using a set of documents

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Uplift modeling and causal inference with machine learning algorithms

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🤖 ⚡ scikit-learn tips

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Deep Survival Machines - Fully Parametric Survival Regression

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MasTrade is a trading bot in baselines3,pytorch,gym

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Masoud Azizi 18 May 24, 2022
Mixing up the Invariant Information clustering architecture, with self supervised concepts from SimCLR and MoCo approaches

Self Supervised clusterer Combined IIC, and Moco architectures, with some SimCLR notions, to get state of the art unsupervised clustering while retain

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Machine Learning Study 혼자 해보기

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Fourier-Bayesian estimation of stochastic volatility models

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Responsible AI Workshop: a series of tutorials & walkthroughs to illustrate how put responsible AI into practice

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Python implementation of Weng-Lin Bayesian ranking, a better, license-free alternative to TrueSkill

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Open Debates Project 156 Dec 14, 2022
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a

Microsoft 14.5k Jan 07, 2023
Module for statistical learning, with a particular emphasis on time-dependent modelling

Operating system Build Status Linux/Mac Windows tick tick is a Python 3 module for statistical learning, with a particular emphasis on time-dependent

X - Data Science Initiative 410 Dec 14, 2022
Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets

Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets Datasets Used: Iris dataset,

Samrat Mitra 2 Nov 18, 2021
XAI - An eXplainability toolbox for machine learning

XAI - An eXplainability toolbox for machine learning XAI is a Machine Learning library that is designed with AI explainability in its core. XAI contai

The Institute for Ethical Machine Learning 875 Dec 27, 2022
Predicting Baseball Metric Clusters: Clustering Application in Python Using scikit-learn

Clustering Clustering Application in Python Using scikit-learn This repository contains the prediction of baseball metric clusters using MLB Statcast

Tom Weichle 2 Apr 18, 2022
Projeto: Machine Learning: Linguagens de Programacao 2004-2001

Projeto: Machine Learning: Linguagens de Programacao 2004-2001 Projeto de Data Science e Machine Learning de análise de linguagens de programação de 2

Victor Hugo Negrisoli 0 Jun 29, 2021
A handy tool for common machine learning models' hyper-parameter tuning.

Common machine learning models' hyperparameter tuning This repo is for a collection of hyper-parameter tuning for "common" machine learning models, in

Kevin Hu 2 Jan 27, 2022