Amazon Rekognition might be a bit more popular than Deepnote. We know about 33 links to it since March 2021 and only 32 links to Deepnote. 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.
AWS Rekognition is a great choice for many types of real-world projects or just for testing an idea on your images. The issue eventually comes with its cost, unfortunately, which we will see later in a specific example. Don’t get me wrong, Rekognition is a great service and I love to use it for its simplicity and reliable performance on quite a few projects. - Source: dev.to / about 2 months ago
I don’t really want to spend so much time manually adjusting labels. For most machine learning, the next step would be to fine tune your model. You can essentially fine tune Amazon Rekognition by using Custom Labels. You can do this to make it better at detecting specific objects (like bears) or train it to detect new objects like your product or logo. It really depends on your application needs. - Source: dev.to / 10 months ago
For instance, are you a company with lots of security cameras? Hire me to write a program that pipes your data into AWS rekognition and then shows you a dashboard of what happened on your cams today. Got a ton of products with no meta-description? Hire me to write a program that pipes your data into OpenAI, and then saves the generated description to your custom CMS. Source: 11 months ago
Amazon Rekognition: Used to index, detect faces in the picture, and compare faces when users try voting, it was the heart of the facial voting feature. - Source: dev.to / about 1 year ago
Sure. But if you think generating thumbnails and detecting intros/credits takes a long time, wait until your computer is running machine learning/computer vision over your entire library. They also have to build and train that model which is no trivial task. And I know what you're thinking, why don't they just use Amazon's Rekognition service that does celebrity identification? Well, it's $0.10 per minute of... Source: about 1 year 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 / 4 months 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 / 11 months ago
Upload your ipynb to Deepnote and publish as an app. That simple. https://deepnote.com. - Source: Hacker News / about 1 year ago
Using Deepnote, we'll create a Python notebook and upload the two GeoJSON files into a data directory. - Source: dev.to / over 1 year ago
Deepnote - A new kind of data science notebook. Jupyter-compatible with real-time collaboration and running in the cloud. Free tier includes unlimited personal projects, up to 750 hours of standard hardware and teams with up to 3 editors. - Source: dev.to / over 1 year ago
Google Vision AI - Cloud Vision API provides a comprehensive set of capabilities including object detection, ocr, explicit content, face, logo, and landmark detection.
Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.
Clarifai - The World's AI
Apache Zeppelin - A web-based notebook that enables interactive data analytics.
Kairos - Facial recognition & mood detection API
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.