MLflow

What is MLflow?

MLflow is an open source platform for managing the end-to-end machine learning lifecycle.

MLflow is a tool in the Development & Training category of a tech stack.

Key Features

Track experiments to record and compare parameters and resultsPackage ML code in a reusable, reproducible form in order to share with other data scientists or transfer to productionManage and deploy models from a variety of ML libraries to a variety of model serving and inference platforms

MLflow Pros & Cons

Pros of MLflow

✓Code First
✓Simplified Logging

Cons of MLflow

No cons listed yet.

MLflow Integrations

Neptune, Databricks, DAGsHub, Truss, Flyte are some of the popular tools that integrate with MLflow. Here's a list of all 5 tools that integrate with MLflow.

MLflow Discussions

Discover why developers choose MLflow. Read real-world technical decisions and stack choices from the StackShare community.

Murali Nagaraj

Jan 11, 2024

Needs adviceon

MLflow

Kubernetes

Kubeflow

We are trying to standardise DevOps across both ML (model selection and deployment) and regular software. Want to minimise the number of tools we have to learn. Also want a scalable solution which is easy enough to start small - eg. on a powerful laptop and eventually be deployed at scale. MLflow vs Kubernetes (Kubeflow)?

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Biswajit Pathak

Project Manager

Sep 13, 2021

Needs adviceon

FastText

Gensim

MLflow

Can you please advise which one to choose FastText Or Gensim, in terms of:

Operability with ML Ops tools such as MLflow, Kubeflow, etc.
Performance
Customization of Intermediate steps
FastText and Gensim both have the same underlying libraries
Use cases each one tries to solve
Unsupervised Vs Supervised dimensions
Ease of Use.

Please mention any other points that I may have missed here.

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Hamid Ghader

Jun 17, 2021

Needs adviceon

DVC

MLflow

I already use DVC to keep track and store my datasets in my machine learning pipeline. I have also started to use MLflow to keep track of my experiments. However, I still don't know whether to use DVC for my model files or I use the MLflow artifact store for this purpose. Or maybe these two serve different purposes, and it may be good to do both! Can anyone help, please?

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MLflow Alternatives & Comparisons

What are some alternatives to MLflow?

TensorFlow

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

NumPy

Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.

Jupyter

The Jupyter Notebook is a web-based interactive computing platform. The notebook combines live code, equations, narrative text, visualizations, interactive dashboards and other media.

MLflow

What is MLflow?

Key Features

MLflow Pros & Cons

Pros of MLflow

Cons of MLflow

MLflow Integrations

MLflow Discussions

MLflow Alternatives & Comparisons

TensorFlow

NumPy

Jupyter

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Adoption

On StackShare

Pandas

PyTorch

scikit-learn

MLflow Integrations

MLflow Discussions

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Adoption

On StackShare