
Algorithmia
MCenter
5Analytics
Spell
neptune.ai
MuleSoft Anypoint Platform
Zapier
Datadog
Deepnote
Apache Zeppelin
Saturn Cloud
Amazon SageMaker
Databricks Unified Analytics Platform
Azure Synapse Analytics
Google BigQuery
GeoSpock
Algorithmia
DeepnoteAlgorithmia is recommended for data scientists, machine learning engineers, and developers who need a flexible and scalable environment to deploy, manage, and share AI and machine learning models. It is particularly suitable for teams seeking to collaborate and leverage pre-built algorithms from a community-driven marketplace. Businesses looking to integrate machine learning capabilities into their operations without extensive infrastructure management will also benefit from Algorithmia's offerings.
Based on our record, Deepnote should be more popular than Algorithmia. It has been mentiond 34 times since March 2021. 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.
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 4 years ago
And for enterprises that want to do the same with ML you can use algorithmia.com. Source: over 4 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 4 years ago
Seems similar to https://algorithmia.com. Source: over 4 years ago
Algorithmia.com โ Host algorithms for free. Includes free monthly allowance for running algorithms. Now with CLI support. - Source: dev.to / almost 5 years ago
Thank you for the list - I think I've come across all of these in my research! I'll try highlight the differences for each. - https://noteable.io/ - as you say, it doesn't exist anymore - https://deepnote.com - I actually mentioned this in the post but in my experience, the UX and features far behind what we've built already. I'd love to hear from anyone who's tried jupyter-ai to give us a shot and let me know... - Source: Hacker News / about 2 years ago
- https://deepnote.com -- also extensive AI integration and realtime collaboration. - Source: Hacker News / about 2 years ago
Deepnote - A new data science notebook. Jupyter is compatible with real-time collaboration and running in the cloud. The free tier includes unlimited personal projects, up to 750 hours of standard hardware, and teams with up to 3 editors. - Source: dev.to / over 2 years ago
We looked into many of these issues with Deepnote (YC S19) [https://deepnote.com/]. What we found is that these are not necessarily problems of the underlying medium (a notebook), but more of the specific implementation (Jupyter). We've seen a lot of progress in the Jupyter ecosystem, but unfortunately almost none in the areas you mentioned. - Source: Hacker News / about 3 years ago
Upload your ipynb to Deepnote and publish as an app. That simple. https://deepnote.com. - Source: Hacker News / over 3 years ago
MCenter - Machine Learning Operationalization
Apache Zeppelin - A web-based notebook that enables interactive data analytics.
5Analytics - The 5Analytics AI platform enables you to use artificial intelligence to automate important commercial decisions and implement digital business models.
Saturn Cloud - ML in the cloud. Loved by Data Scientists, Control for IT. Advance your business's ML capabilities through the entire experiment tracking lifecycle. Available on multiple clouds: AWS, Azure, GCP, and OCI.
Spell - Deep Learning and AI accessible to everyone
Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.