Based on our record, Microsoft Azure seems to be a lot more popular than Algorithmia. While we know about 65 links to Microsoft Azure, 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.
The first step in creating a virtual machine is getting a Microsoft account. Once you have a Microsoft account click this link to create an Azure free trial account. Click on the "Try Azure for free" button. This takes you to the page below. - Source: dev.to / about 2 months ago
Before you start, ensure you have an active Azure subscription, if you don't have one, Click here to create a free account. - Source: dev.to / 3 months ago
A VM is the original “hosting” product of the cloud era. Over the last 20 years, VM providers have come and gone, as have enterprise virtualization solutions such as VMware. Today you can do this somewhere like OVHcloud, Hetzner or DigitalOcean, which took over the “server” market from the early 2000’s. Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft's Azure also offer VMs, at a less... - Source: dev.to / 5 months ago
Before deploying the application with Kubernetes, you need to containerize the application using docker. This article shows how to deploy a Flask application on Ubuntu 22.04 using Minikube; a Kubernetes tool for local deployment for testing and free offering. Alternatively, you can deploy your container apps using Cloud providers such as GCP(Google Cloud), Azure(Microsoft) or AWS(Amazon). - Source: dev.to / 5 months ago
Consider cloud storage services for offsite storage and automation (Azure, AWS, GCP). - Source: dev.to / 10 months 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
Amazon AWS - Amazon Web Services offers reliable, scalable, and inexpensive cloud computing services. Free to join, pay only for what you use.
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.
DigitalOcean - Simplifying cloud hosting. Deploy an SSD cloud server in 55 seconds.
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.
Linode - We make it simple to develop, deploy, and scale cloud infrastructure at the best price-to-performance ratio in the market.Sign up to Linode through SaaSHub and get a $100 in credit!
MCenter - Machine Learning Operationalization