Hasty’s end-to-end AI platform helps automate and accelerate the whole life-cycle of implementing vision AI in real life for agricultural, manufacturing, logistic, mining, and other industrial companies. Our data-centric platform allows companies with unique data to build and deploy vision AI applications faster and more reliably across any infrastructure – helping you bring value-added services to your product.
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Based on our record, Keras seems to be a lot more popular than Hasty.ai. While we know about 31 links to Keras, we've tracked only 2 mentions of Hasty.ai. 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 / 11 days 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 / 20 days 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 / 11 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: 12 months 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
Try https://hasty.ai, seems to be pretty much exactly what you're looking for. Source: over 2 years ago
At hasty.ai, we're working on agile ML tooling for vision AI to help our users get to production more reliably. A huge part of this is to automate and speed the data preparation process. 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.
Labelbox - Build computer vision products for the real world
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Supervisely - Supervisely helps people with and without machine learning expertise to create state-of-the-art...
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
CrowdFlower - Enterprise crowdsourcing for micro-tasks