Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...

Overview

MLOps Platforms

MLOps is an especially confusing landscape with hundreds of tools available. This project helps to navigate the space of MLOps platforms.

Understanding MLOps platforms is complex. Platforms have their own specializations and there is no clear line between a tool (with a narrow focus) and a platform (which supports many ML lifecycle activities). The below (from the Thoughtworks Guide to MLOps Platforms) illustrates how some of the platforms specialize in particular areas (bottom) and others aim to cover the whole lifecycle with equal focus (top):

MLOps Landscape Diagram

Even platforms that have a similar scope have different concepts and strategies, making them hard to compare directly. This repository provides resources for evaluating MLOps platforms.

If you're wondering what process to use to evaluate MLOps platforms, see the Thoughtworks Guide. If you know how to evaluate MLOps platforms and want materials, read on.

Comparison Matrix Format

The matrix an open format of categories with links to vendor documentation within cells to highlight features. This lets vendors do things their own ways and helps readers find the detail they need.

Comparison Matrix

We suggest to click through to the master spreadsheet in google sheets:

matrix

If you can't access or don't like google sheets then there is a translation of the matrix into Github markdown

Platform Profiles

These profiles are concise marketing-free introductions to key concepts of MLOps platforms. This provides just enough context to make sense of the features in the matrix.

Contributions

Everyone is welcome to contribute, including vendors. Language should be neutral - marketing language will not be accepted.

Changes are welcome by PR or issues - please create a copy of the spreadsheet, link to or upload your copy and explain which parts are changed. Please follow the existing format or raise an issue in advance to suggest changes to the format. On approval a maintainer will then update the master spreadsheet used to generate the markdown.

Disclaimer

We do our best to keep this information accurate and up-to-date but cannot provide guarantees. References to documentation are provided throughout so readers can check for themselves. If you spot anything inaccurate then please raise an issue or pull request (see Contributing section).

Owner
Thoughtworks
Thoughtworks
Random Forest Classification for Neural Subtypes

Random Forest classifier for neural subtypes extracted from extracellular recordings from human brain organoids.

Michael Zabolocki 1 Jan 31, 2022
Pandas-method-chaining is a plugin for flake8 that provides method chaining linting for pandas code

pandas-method-chaining pandas-method-chaining is a plugin for flake8 that provides method chaining linting for pandas code. It is a fork from pandas-v

Francis 5 May 14, 2022
Relevance Vector Machine implementation using the scikit-learn API.

scikit-rvm scikit-rvm is a Python module implementing the Relevance Vector Machine (RVM) machine learning technique using the scikit-learn API. Quicks

James Ritchie 204 Nov 18, 2022
Climin is a Python package for optimization, heavily biased to machine learning scenarios

climin climin is a Python package for optimization, heavily biased to machine learning scenarios distributed under the BSD 3-clause license. It works

Biomimetic Robotics and Machine Learning at Technische Universität München 177 Sep 02, 2022
Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)

Little Ball of Fur is a graph sampling extension library for Python. Please look at the Documentation, relevant Paper, Promo video and External Resour

Benedek Rozemberczki 619 Dec 14, 2022
Factorization machines in python

Factorization Machines in Python This is a python implementation of Factorization Machines [1]. This uses stochastic gradient descent with adaptive re

Corey Lynch 892 Jan 03, 2023
Backtesting an algorithmic trading strategy using Machine Learning and Sentiment Analysis.

Trading Tesla with Machine Learning and Sentiment Analysis An interactive program to train a Random Forest Classifier to predict Tesla daily prices us

Renato Votto 31 Nov 17, 2022
Tools for diffing and merging of Jupyter notebooks.

nbdime provides tools for diffing and merging of Jupyter Notebooks.

Project Jupyter 2.3k Jan 03, 2023
MIT-Machine Learning with Python–From Linear Models to Deep Learning

MIT-Machine Learning with Python–From Linear Models to Deep Learning | One of the 5 courses in MIT MicroMasters in Statistics & Data Science Welcome t

2 Aug 23, 2022
🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams

🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams

Real-time water systems lab 416 Jan 06, 2023
Module is created to build a spam filter using Python and the multinomial Naive Bayes algorithm.

Naive-Bayes Spam Classificator Module is created to build a spam filter using Python and the multinomial Naive Bayes algorithm. Main goal is to code a

Viktoria Maksymiuk 1 Jun 27, 2022
customer churn prediction prevention in telecom industry using machine learning and survival analysis

Telco Customer Churn Prediction - Plotly Dash Application Description This dash application allows you to predict telco customer churn using machine l

Benaissa Mohamed Fayçal 3 Nov 20, 2021
Python bindings for MPI

MPI for Python Overview Welcome to MPI for Python. This package provides Python bindings for the Message Passing Interface (MPI) standard. It is imple

MPI for Python 604 Dec 29, 2022
Python module for performing linear regression for data with measurement errors and intrinsic scatter

Linear regression for data with measurement errors and intrinsic scatter (BCES) Python module for performing robust linear regression on (X,Y) data po

Rodrigo Nemmen 56 Sep 27, 2022
Python library which makes it possible to dynamically mask/anonymize data using JSON string or python dict rules in a PySpark environment.

pyspark-anonymizer Python library which makes it possible to dynamically mask/anonymize data using JSON string or python dict rules in a PySpark envir

6 Jun 30, 2022
Spark development environment for k8s

Local Spark Dev Env with Docker Development environment for k8s. Using the spark-operator image to ensure it will be the same environment. Start conta

Otacilio Filho 18 Jan 04, 2022
Machine learning template for projects based on sklearn library.

Machine learning template for projects based on sklearn library.

Janez Lapajne 17 Oct 28, 2022
SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and TensorFlow

SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and TensorFlow, in High Performance Computing (HPC) simulations and workloads.

A Microsoft Azure Web App project named Covid 19 Predictor using Machine learning Model

A Microsoft Azure Web App project named Covid 19 Predictor using Machine learning Model (Random Forest Classifier Model ) that helps the user to identify whether someone is showing positive Covid sym

Priyansh Sharma 2 Oct 06, 2022
Laporan Proyek Machine Learning - Azhar Rizki Zulma

Laporan Proyek Machine Learning - Azhar Rizki Zulma Project Overview Domain proyek yang dipilih dalam proyek machine learning ini adalah mengenai hibu

Azhar Rizki Zulma 6 Mar 12, 2022