Labelbox
V7
Supervisely
Playment
CloudFactory
Hive
Amazon Mechanical Turk
Universal Data Tool
Amazon AWS
DigitalOcean
Microsoft Azure
Linode
GoDaddy
Google Cloud Platform
Vultr
Heroku
A complete solution for your training data problem with fast labeling tools, human workforce, data management, a powerful API and automation features.
Labelbox Amazon AWSService goes down often. Very slow team. Slow support.
You could say a lot of things about AWS, but among the cloud platforms (and I've used quite a few) AWS takes the cake. It is logically structured, you can get through its documentation relatively easily, you have a great variety of tools and services to choose from [from AWS itself and from third-party developers in their marketplace]. There is a learning curve, there is quite a lot of it, but it is still way easier than some other platforms. I've used and abused AWS and EC2 specifically and for me it is the best.
Based on our record, Amazon AWS seems to be a lot more popular than Labelbox. While we know about 370 links to Amazon AWS, we've tracked only 8 mentions of Labelbox. 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.
Labelbox | Remote | Frontend / WebGL, Backend, Engineering Managers | https://labelbox.com Labelbox is building the training data platform to power breakthroughs in machine learning. We provide an end to end solutions for the full AI lifecycle from creating catalogs of unstructured data all the way to building the tools for humans to label the data to teach machines. Why choose us? - Source: Hacker News / over 1 year ago
Hey, I have currently developed a U-Net model for segmentation and I am trying to use the model assisted labeling feature on LabelBox to annotate some masks, so I can save time on relabeling. I am just wondering if anyone is familiar with this feature or can give me a step by step guideline on how to go about doing this. I went through the examples on their GitHub but I’m honestly still very confused. Any help... Source: almost 2 years ago
By now, I hope you see where I'm going with this. What is MDR doing? They're creating the labelled data used to train severance chips. They get a raw download of human brains in encoded format, and go about manually labelling the different pieces based on their most basic elements. Then, based on this manually labelled data, an algorithm can be trained to create a severance chip. MDR is basically Labelbox for... Source: about 2 years ago
LabelBox - they provide free versions for research. Source: about 2 years ago
Doing some progress, labelbox.com allows me to do the Video annotation, and access all data through python SDK/API... Working on converting myself to CSV GCP format :-). Source: over 2 years ago
Heroku runs on top of Amazon Web Services (AWS). Key benefits for me are:. - Source: dev.to / 14 days ago
First navigate to AWS at - https://aws.amazon.com create an account and then on the dashboard search for Amazon SES, click get started and then you should be directed to a dashboard like this. - Source: dev.to / 15 days ago
AWS Account Setup: If you don't have one, you can create a free account. - Source: dev.to / 18 days ago
Amazon Web Services is a leading cloud platform offering a vast array of services, from compute and storage to machine learning and IoT. AWS is known for its scalability, handling anything from small projects to enterprise-level applications. - Source: dev.to / 24 days ago
In this tutorial, I will walk you through building a quick static site by doing a static build using ReactJS & create-react-app, then show you how to deploy that static site on AWS using S3 buckets as well as how to cache it & add SSL certificates with CloudFront CDN & Certificate Manager. - Source: dev.to / 24 days ago
V7 - Pixel perfect image labeling for industrial, medical, and large scale dataset creation. Create ground truth 10 times faster.
DigitalOcean - Simplifying cloud hosting. Deploy an SSD cloud server in 55 seconds.
Supervisely - Supervisely helps people with and without machine learning expertise to create state-of-the-art...
Microsoft Azure - Windows Azure and SQL Azure enable you to build, host and scale applications in Microsoft datacenters.
Playment - Playment is a fully-managed solution offering training data for AI, transcription, data collection and enrichment services at scale.
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!
