We built a fascinating platform, https://iko.ai, that allows you to train, track, package, deploy, and monitor machine learning models with real-time collaborative notebooks on your own Kubernetes clusters. Source: almost 2 years ago

Hi, Edwin. I'm in the process of integrating Stripe to https://iko.ai. I recently discovered Portal (https://stripe.com/docs/billing/subscriptions/integrating-customer-portal) and I thank you for that. Less code for me. I'm a bit ashamed to say, but I'm having trouble with checking if the customer has a valid subscription. I'm currently only storing the customer_id in the database and retrieving the information... - Source: Hacker News / about 2 years ago

That was one the reasons we do "bring your own compute" with https://iko.ai so people who already have a billing account on AWS, GCP, Azure, DigitalOcean, can just get the config for their Kubernetes clusters and link them to iko.ai and their machine learning workloads will run on whichever cluster they select. If you get a good deal from one cloud provider, you can get started quickly. It's useful even for... - Source: Hacker News / about 2 years ago

We built an internal platform to streamline this that allows us to train, package, deploy, and monitor models (very shameless plug for our product https://iko.ai that we started because I was tired of watching colleagues look from the window to see if their train was here because they had to come to the office to train their model on the "powerful machine" and they spent 6 hours in commute every day and at some... Source: about 2 years ago

We built https://iko.ai which offers real-time collaborative notebooks to train, track, package, deploy, and monitor machine learning models. Source: over 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 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