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MLflow Alternatives
Similar projects and alternatives to MLflow
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InfluxDB
Build time-series-based applications quickly and at scale.. InfluxDB is the Time Series Platform where developers build real-time applications for analytics, IoT and cloud-native services. Easy to start, it is available in the cloud or on-premises.
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Sacred
Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
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clearml
ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management
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Prophet
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
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Sonar
Write Clean Python Code. Always.. Sonar helps you commit clean code every time. With over 225 unique rules to find Python bugs, code smells & vulnerabilities, Sonar finds the issues while you focus on the work.
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Pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
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H2O
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.
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fastapi
FastAPI framework, high performance, easy to learn, fast to code, ready for production
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Airflow
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
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PostgreSQL
Mirror of the official PostgreSQL GIT repository. Note that this is just a *mirror* - we don't work with pull requests on github. To contribute, please see https://wiki.postgresql.org/wiki/Submitting_a_Patch
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MySQL
MySQL Server, the world's most popular open source database, and MySQL Cluster, a real-time, open source transactional database.
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catboost
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better MLflow alternative or higher similarity.
MLflow reviews and mentions
Posts with mentions or reviews of MLflow.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-12.
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ML experiment tracking with DagsHub, MLFlow, and DVC
Here, we’ll implement the experimentation workflow using DagsHub, Google Colab, MLflow, and data version control (DVC). We’ll focus on how to do this without diving deep into the technicalities of building or designing a workbench from scratch. Going that route might increase the complexity involved, especially if you are in the early stages of understanding ML workflows, just working on a small project, or trying to implement a proof of concept.
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AI in DevOps?
MLflow
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AWS re:invent 2022 wish list
I am seeing growing demand for MLflow (https://mlflow.org/) and I am seeing a lot of people looking at Databricks as commercial offering for MLflow. Alternatively, some popele are implementing something like Managing your Machine Learning lifecycle with MLflow. Therefore, I think this was on my wish list last year, but I really hope AWS announce a Managed MLFlow Service. I know version 2.X is too new but at least 1.X would be great start.
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✨ 7 Best Machine Learning Experiment Logging Tools in 2022 🚀
🔗 https://mlflow.org
- [D] Who here are convinced that they have a really good setup that keeps track of their ML experiments?
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JBCNConf 2022: A great farewell
She made mentions to ML-Ops and MLFlow including Vertex AI the GCP implementation. I will post the video as soon as it is available. In the meantime, you can enjoy any other talk from Nerea Luis
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Keeping Your Machine Learning Models on the Right Track: Getting Started with MLflow, Part 2
In our last post, we discussed the importance of tracking Machine Learning experiments, metrics and parameters. We also showed how easy it is to get started in these topics by leveraging the power of MLflow (for those who are not aware, MLflow is currently the de-facto standard platform for machine learning experiment and model management).
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MLflow VS VevestaX - a user suggested alternative
2 projects | 12 May 2022
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MLOps with MLflow on Kraken CI
Besides building, testing and deploying, Kraken CI is also a pretty nice tool to build an MLOps pipeline. In this article, it will be shown how to leverage Kraken CI to build a CI workflow for machine learning using MLflow.
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Serving Python Machine Learning Models With Ease
For MLFlow users you can now serve models directly in MLFlow using MLServer and if you're a Kubernetes user you should definitely check out Seldon Core - an open source tool that deploys models to Kubernetes (it uses MLServer under the covers).
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A note from our sponsor - #<SponsorshipServiceOld:0x00007fea59ab92f8>
www.saashub.com | 2 Feb 2023
Stats
Basic MLflow repo stats
36
13,535
9.7
5 days ago
mlflow/mlflow is an open source project licensed under Apache License 2.0 which is an OSI approved license.
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