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Learn MorePros of MLflow
Pros of Postman
Pros of MLflow
- Code First5
- Simplified Logging4
Pros of Postman
- Easy to use490
- Great tool369
- Makes developing rest api's easy peasy276
- Easy setup, looks good156
- The best api workflow out there144
- It's the best53
- History feature53
- Adds real value to my workflow44
- Great interface that magically predicts your needs43
- The best in class app35
- Can save and share script12
- Fully featured without looking cluttered10
- Collections8
- Option to run scrips8
- Global/Environment Variables8
- Shareable Collections7
- Dead simple and useful. Excellent7
- Dark theme easy on the eyes7
- Awesome customer support6
- Great integration with newman6
- Documentation5
- Simple5
- The test script is useful5
- Saves responses4
- This has simplified my testing significantly4
- Makes testing API's as easy as 1,2,34
- Easy as pie4
- API-network3
- I'd recommend it to everyone who works with apis3
- Mocking API calls with predefined response3
- Now supports GraphQL2
- Postman Runner CI Integration2
- Easy to setup, test and provides test storage2
- Continuous integration using newman2
- Pre-request Script and Test attributes are invaluable2
- Runner2
- Graph2
- <a href="http://fixbit.com/">useful tool</a>1
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Cons of MLflow
Cons of Postman
Cons of MLflow
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Cons of Postman
- Stores credentials in HTTP10
- Bloated features and UI9
- Cumbersome to switch authentication tokens8
- Poor GraphQL support7
- Expensive5
- Not free after 5 users3
- Can't prompt for per-request variables3
- Import swagger1
- Support websocket1
- Import curl1
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What is MLflow?
MLflow is an open source platform for managing the end-to-end machine learning lifecycle.
What is Postman?
It is the only complete API development environment, used by nearly five million developers and more than 100,000 companies worldwide.
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What companies use MLflow?
What companies use Postman?
What companies use MLflow?
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What tools integrate with MLflow?
What tools integrate with Postman?
What tools integrate with MLflow?
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What are some alternatives to MLflow and Postman?
Kubeflow
The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.
Airflow
Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
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.
DVC
It is an open-source Version Control System for data science and machine learning projects. It is designed to handle large files, data sets, machine learning models, and metrics as well as code.
Seldon
Seldon is an Open Predictive Platform that currently allows recommendations to be generated based on structured historical data. It has a variety of algorithms to produce these recommendations and can report a variety of statistics.