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
List of Data Science Cheatsheets to rule the world

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Favio André Vázquez 11.7k Dec 30, 2022
Used Logistic Regression, Random Forest, and XGBoost to predict the outcome of Search & Destroy games from the Call of Duty World League for the 2018 and 2019 seasons.

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This machine learning model was developed for House Prices

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serhat_derya 1 Mar 02, 2022
Data science, Data manipulation and Machine learning package.

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[HELP REQUESTED] Generalized Additive Models in Python

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Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning

Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning. It features an imperative, define-by-run style user API.

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Getting Profit and Loss Make Easy From Binance

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Simple Machine Learning Tool Kit

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Model factory is a ML training platform to help engineers to build ML models at scale

Model Factory Machine learning today is powering many businesses today, e.g., search engine, e-commerce, news or feed recommendation. Training high qu

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This is an auto-ML tool specialized in detecting of outliers

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Pydantic based mock data generation

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Na'aman Hirschfeld 396 Dec 28, 2022
NumPy-based implementation of a multilayer perceptron (MLP)

My own NumPy-based implementation of a multilayer perceptron (MLP). Several of its components can be tuned and played with, such as layer depth and size, hidden and output layer activation functions,

1 Feb 10, 2022
The unified machine learning framework, enabling framework-agnostic functions, layers and libraries.

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The project's goal is to show a real world application of image segmentation using k means algorithm

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Case studies with Bayesian methods

Case studies with Bayesian methods

Baze Petrushev 8 Nov 26, 2022
Class-imbalanced / Long-tailed ensemble learning in Python. Modular, flexible, and extensible

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Zhining Liu 176 Jan 04, 2023
This machine-learning algorithm takes in data from the last 60 days and tries to predict tomorrow's price of any crypto you ask it.

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