Apple Core ML
Amazon Machine Learning
TensorFlow Lite
Roboflow Universe
ML5.js
Machine Learning Playground
Apple Machine Learning Journal
QuickAI
Saturn Cloud
Amazon SageMaker
Deepnote
Apache Zeppelin
Databricks Unified Analytics Platform
GeoSpock
Azure Synapse Analytics
Google BigQuery
Saturn Cloud is an award-winning ML platform with 75,000+ users, including NVIDIA, CFA Institute, Snowflake, Flatiron School, Nestle, and more. It is an all-in-one solution for data science & ML development, deployment, and data pipelines in the cloud. Users can spin up a notebook with 4TB of RAM, add a GPU, connect to a distributed cluster of workers, build large language models, and more in a completely hosted environment.
Data scientists and analysts work best using the tools they want to use. You can use your preferred languages, IDEs, and machine-learning libraries in Saturn Cloud. We offer full Git integration, shared custom images, and secure credential storage, making scaling and building your team in the cloud easy. We support the entire machine learning lifecycle from experimentation to production with features like jobs and deployments. These features and built-in tools are easily shareable within teams, so time is saved and work is reproducible.
Apple Core MLSmooth and bug free experience. There are ready data science images with pre loaded packages for most common scenarios, making you focus on the project/problem and leave the infrastructure part to Saturn Cloud.
True story, way better than just sweating Colab. The best and cheapest compute services there is.
I have started using this to run the computations which generally require like 64+GB of RAM, and the procedure to setup the enviroment is also nice. Got all the R packages running smoothly.
Apple Core ML might be a bit more popular than Saturn Cloud. We know about 7 links to it since March 2021 and only 6 links to Saturn Cloud. 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.
On the machine learning side of AI, they have CoreML. You can drag-and-drop images into Xcode to train an image classifier. And run the models on device, so if solar flares destroy the cell phone network and terrorists bomb all the data centers, your phone could still tell you if it's a hot dog or not. https://developer.apple.com/machine-learning/ https://developer.apple.com/machine-learning/core-ml/... - Source: Hacker News / 2 months ago
Apple has actually created ML chipsets, so AI can be executed natively, on-device. https://developer.apple.com/machine-learning/. - Source: Hacker News / 4 months ago
For your reference, Apple's pages for Machine Learning for Developers and for their research. The Apple Neural Engine was custom designed to work better with their proprietary machine learning programs -- and they've been opening up access to developers by extending support / compatibility for TensorFlow and PyTorch. They've also got CoreML, CreateML, and various APIs they are making to allow more use of their... Source: 12 months ago
> It’d be one thing if Apple actually worked on AI softwares a bit and made it readily available to developers. * Apple Silicon CPUs have a Neural Engine specifically made for fast ML-inference * Apple supports PyTorch (https://developer.apple.com/metal/pytorch/) * Apple has its own easily accessible machine-learning framework called Core-ML (https://developer.apple.com/machine-learning/) So it would be inaccurate... - Source: Hacker News / about 1 year ago
This is the developer documentation where they advertise the APIs - https://developer.apple.com/machine-learning/. Source: over 2 years ago
Not 100% sure of your intention, but if you work with python, and you're familiar with (or can spend the time learning) dask, and willing to pay, you can consider coiled.io or saturncloud.io that offer managed dask that you can scale and use GPUs etc (again, not sure if applicable to your use case). Source: about 1 year ago
SaturnCloud - Data science cloud environment, that allows to run Jupyter notebooks and Dask clusters. 30 hours free computation and 3 hours of Dask per month. - Source: dev.to / over 1 year ago
I think your site looks good and I have used the type of service you offer, but there are 2 potential problems. As SheepherderPatient51 said,Google already offers all of this for free (and so does https://kaggle.com and https://www.paperspace.com ). There are also other sites just like yours such as https://deepnote.com,https://saturncloud.io, and https://lambdalabs.com . Source: over 1 year ago
* How does it differ from other GPU cloud providers that offer ready to use Jupyter notebooks? (E.g. https://support.genesiscloud.com/support/solutions/articles/47001170102-running-jupyter-notebook-or-jupyterlab-on-your-instance or https://saturncloud.io/). - Source: Hacker News / about 2 years ago
At the moment I am going to go to https://saturncloud.io/ or https://www.cloudeo.group/. Source: over 2 years ago
Amazon Machine Learning - Machine learning made easy for developers of any skill level
Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.
TensorFlow Lite - Low-latency inference of on-device ML models
Deepnote - A collaboration platform for data scientists
Roboflow Universe - You no longer need to collect and label images or train a ML model to add computer vision to your project.
Apache Zeppelin - A web-based notebook that enables interactive data analytics.