Need advice about which tool to choose?Ask the StackShare community!

Comet.ml

12
48
+ 1
3
MLflow

174
490
+ 1
9
Add tool

Comet.ml vs MLflow: What are the differences?

Developers describe Comet.ml as "Track, compare and collaborate on Machine Learning experiments". Comet.ml allows data science teams and individuals to automagically track their datasets, code changes, experimentation history and production models creating efficiency, transparency, and reproducibility. On the other hand, MLflow is detailed as "An open source machine learning platform". MLflow is an open source platform for managing the end-to-end machine learning lifecycle.

Comet.ml and MLflow can be primarily classified as "Machine Learning" tools.

MLflow is an open source tool with 20 GitHub stars and 11 GitHub forks. Here's a link to MLflow's open source repository on GitHub.

Get Advice from developers at your company using StackShare Enterprise. Sign up for StackShare Enterprise.
Learn More
Pros of Comet.ml
Pros of MLflow
  • 3
    Best tool for comparing experiments
  • 5
    Code First
  • 4
    Simplified Logging

Sign up to add or upvote prosMake informed product decisions

- No public GitHub repository available -

What is Comet.ml?

Comet.ml allows data science teams and individuals to automagically track their datasets, code changes, experimentation history and production models creating efficiency, transparency, and reproducibility.

What is MLflow?

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

Need advice about which tool to choose?Ask the StackShare community!

What companies use Comet.ml?
What companies use MLflow?
See which teams inside your own company are using Comet.ml or MLflow.
Sign up for StackShare EnterpriseLearn More

Sign up to get full access to all the companiesMake informed product decisions

What tools integrate with Comet.ml?
What tools integrate with MLflow?

Sign up to get full access to all the tool integrationsMake informed product decisions

What are some alternatives to Comet.ml and 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.
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
Keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
CUDA
A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.
See all alternatives