Keras
TensorFlow
PyTorch
Scikit-learn
OpenCV
TFlearn
Clarifai
DeepPy
Aquarium
Scale Nucleus
PerceptiLabs
ML Image Classifier
Roboflow Universe
Google Cloud TPUs
Prodigy
Stack Roboflow
AquariumBased on our record, Keras seems to be a lot more popular than Aquarium. While we know about 31 links to Keras, we've tracked only 2 mentions of Aquarium. 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.
As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development. - Source: dev.to / about 1 month ago
After setting the variables for the environment, the next step is to install dependencies. To use Gemma, KerasNLP is the dependency used. KerasNLP is a collection of natural language processing (NLP) models implemented in Keras and runnable on JAX, PyTorch, and TensorFlow. - Source: dev.to / about 2 months ago
Other popular machine learning tools include PyTorch, Keras, and Scikit-learn. PyTorch is an open-source machine learning library developed by Facebook that is known for its ease of use and flexibility. Keras is a high-level neural networks API that is written in Python and is known for its simplicity. Scikit-learn is a machine learning library for Python that is used for data analysis and data mining tasks. - Source: dev.to / 12 months ago
I'm not aware of anything off-the-shelf, but if you have sufficient programming experience, one way to do this would be to build a large dataset of reference images and pictures and use something like keras to train a convolutional neural network on them. Source: about 1 year ago
Pandas comes with many complex tabular data operations. And, since it exists in a Python environment, it can be coupled with lots of other powerful libraries, such as Requests (for connecting to other APIs), Matplotlib (for plotting data), Keras (for training machine learning models), and many more. - Source: dev.to / over 1 year 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: almost 3 years ago
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.
Scale Nucleus - The mission control for your ML data
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
PerceptiLabs - A tool to build your machine learning model at warp speed.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
ML Image Classifier - Quickly train custom machine learning models in your browser