Google CLOUD AUTOML
Qubole
BigML
TensorFlow
Scikit-learn
AWS SageMaker Ground Truth
machine-learning in Python
RapidMiner
Aquarium
Scale Nucleus
PerceptiLabs
Roboflow Universe
ML Image Classifier
Prodigy
Google Cloud TPUs
Stack Roboflow
Google CLOUD AUTOML AquariumNo Google CLOUD AUTOML videos yet. You could help us improve this page by suggesting one.
Based on our record, Google CLOUD AUTOML should be more popular than Aquarium. It has been mentiond 6 times since March 2021. 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.
There are several no-code AI websites that you can use like Amazon SageMaker, Apple CreateML or Google AutoML. Source: about 1 year ago
GCP, on the other hand, offers two top options: Google Cloud AutoML, for beginners, and Google Cloud Machine Learning Engine, for handling tasking projects. GCP also provides Tenserflow and Vertex AI complicated machine learning abilities. - Source: dev.to / over 1 year ago
Just outsource the work to Google or Amazon. Source: over 2 years ago
We can also note the appearance of Machine Learning, creating dynamic processes over data that would have been tedious to analyse, either by hand or through specific code. This enables writing potentially complex behaviours with a few lines of code in some cases. Even then, there is some automation of it to the point where you only have to provide data to get working results. - Source: dev.to / almost 3 years ago
You might want to check out automl Google AutoML. Source: almost 3 years ago
Aquarium (https://aquariumlearning.com/) | Remote Only (North American Timezones) | Full Time Aquarium is an ML data management system that helps ML teams improve their models by improving their datasets. Aquarium uncovers problems in your dataset, then helps you edit or add data to fix these problems and optimize your model performance. We are looking for our first Product Manager and are also hiring for... - Source: Hacker News / over 2 years ago
#ML is maturing and teams are less concerned about having enough #data, but rather having the right data. ML data management tooling helps improve ML models by improving datasets. Check out our piece below that discusses trends in the space and startups like aquariumlearning.com, Tryunbox.ai, Lightly.ai, Scale, and Labelbox. https://medium.com/memory-leak/ml-data-management-a-primer-a635a5eac858. Source: over 2 years ago
Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.
Scale Nucleus - The mission control for your ML data
BigML - BigML's goal is to create a machine learning service extremely easy to use and seamless to integrate.
PerceptiLabs - A tool to build your machine learning model at warp speed.
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
Roboflow Universe - You no longer need to collect and label images or train a ML model to add computer vision to your project.