Gitea
GitLab
GitHub
BitBucket
Gogs
GitBucket
GitHub Desktop
RhodeCode
Algorithmia
Managed MLflow
MCenter
neptune.ai
5Analytics
Weights & Biases
Iterative.ai
Comet.ml
AlgorithmiaBased on our record, Gitea seems to be a lot more popular than Algorithmia. While we know about 60 links to Gitea, we've tracked only 5 mentions of Algorithmia. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
This reminds me of Gogs [0], where the original author refused a lot of good ideas and improvements, eventually leading to a fork [1] that's now a lot more popular and active than the original. [0] https://gogs.io/ [1] https://gitea.io/en-us/. - Source: Hacker News / almost 2 years ago
Yes, we do this using https://gitea.io/en-us/ on a private server. Firewall, backups and a replica running for most projects. Github is only used when it's required by a stakeholder. - Source: Hacker News / almost 2 years ago
There's a number of places out there, some of which also support alternatives to Git itself. By no means a complete list and in no particular order: GitLab - https://about.gitlab.com/ Sourcehut - https://sourcehut.org/ Codeberg - https://codeberg.org/ Launchpad - https://launchpad.net/ Debian Salsa - https://salsa.debian.org/public Pagure - https://pagure.io/pagure For self hsoted options, there's these below... - Source: Hacker News / about 2 years ago
And if you need GitLab (for runner, etc...) then it's not too bad to run in Docker. But if anyone is looking for a somewhat simpler git solution, gitea is pretty great. Source: about 2 years ago
Check: Configuration and syntax changes and Special packages. The latter includes changes on PostgreSQL, Python and Gitea. - Source: dev.to / about 2 years ago
To push a model into production, there are additional concerns which the tools in the versioning, deployment and release space aim to solve. This includes obtaining adequate infrastructure to run the model reliably and facilitating easy model release or rollback. Solutions in the MLOps space includes Kubeflow, Pachyderm and Algorithmia. - Source: dev.to / over 3 years ago
And for enterprises that want to do the same with ML you can use algorithmia.com. Source: over 3 years ago
Algorithmia advertises themselves as an MLops platform for data scientists, and they provide an easy way to host models on a scalable REST API. Source: over 3 years ago
Seems similar to https://algorithmia.com. Source: over 3 years ago
Algorithmia.com — Host algorithms for free. Includes free monthly allowance for running algorithms. Now with CLI support. - Source: dev.to / almost 4 years ago
GitLab - Create, review and deploy code together with GitLab open source git repo management software | GitLab
Managed MLflow - Managed MLflow is built on top of MLflow, an open source platform developed by Databricks to help manage the complete Machine Learning lifecycle with enterprise reliability, security, and scale.
GitHub - Originally founded as a project to simplify sharing code, GitHub has grown into an application used by over a million people to store over two million code repositories, making GitHub the largest code host in the world.
MCenter - Machine Learning Operationalization
BitBucket - Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.
neptune.ai - Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.