Algorithmia
Managed MLflow
neptune.ai
MCenter
Datatron
5Analytics
Iterative.ai
Numericcal
Banana.dev
Clever Grid
GPU.LAND
Kobra
mlblocks
Vast.ai
Lobe
Neuro
Algorithmia Banana.devNo Banana.dev videos yet. You could help us improve this page by suggesting one.
Based on our record, Banana.dev should be more popular than Algorithmia. It has been mentiond 13 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 2 years ago
And for enterprises that want to do the same with ML you can use algorithmia.com. Source: over 2 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 2 years ago
Seems similar to https://algorithmia.com. Source: over 2 years ago
Algorithmia.com — Host algorithms for free. Includes free monthly allowance for running algorithms. Now with CLI support. - Source: dev.to / almost 3 years ago
For the inference part, you can dockerise your model and use https://banana.dev for serverless GPU. They have examples on github on how to deploy and I’ve done it last year and was pretty straightforward. - Source: Hacker News / about 1 month ago
I want to first check the user's ID and only if the user has an active subscription then the request will be forwarded to my API on banana.dev else the request will be blocked at the middleware itself. Should I use Express JS for the middleware i.e. Authentication and forwarding requests? Is there any other better way to improve my project structure? Currently it looks like:. Source: 7 months ago
Hey! Would love to have you try https://banana.dev (bias: I'm one of the founders). We run A100s for you and scale 0->1->n->0 on demand, so you only pay for what you use. I'm at erik@banana.dev if you want any help with it :). - Source: Hacker News / about 1 year ago
CAN you do this in AWS? Of course, do they have a service that does exactly what this banana.dev does? Probably not. Source: about 1 year ago
I've been using banana.dev for easily running my ML models on GPU in a serverless manner, and interacting with them as an API. Although the principle of the service is sound, it is currently too buggy to take into production (very long cold boots, errorring requests, always hitting capacity). Source: about 1 year ago
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.
Clever Grid - Easy to use and fairly priced GPUs for Machine Learning
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.
GPU.LAND - Cloud GPUs for Deep Learning — for ⅓ the price!
MCenter - Machine Learning Operationalization
Kobra - Visual programming for machine learning, like Scratch