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Based on our record, Keras should be more popular than ImageKit.io. It has been mentiond 31 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.
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 / 28 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 / about 1 month 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: 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
Having the server decide the image format based on the accept header is simpler. Services like https://imagekit.io/ (no affiliation) can do that for you. - Source: Hacker News / about 1 month ago
Hosting wise, I would reccomend pythonanywhere.com, combined with either https://imagekit.io or https://cloudinary.com. Source: about 1 year ago
Use any third-party service to store images like Cloudinary , imagekit etc... And store image URLs in your database. If you have fewer images you keep image URLs directly in your APIs. Source: over 1 year ago
Imagekit.io – Image CDN with automatic optimization, real-time transformation, and storage that you can integrate with existing setup in minutes. Free plan includes up to 20GB bandwidth per month. - Source: dev.to / over 1 year ago
We'll be using Multer to handle file uploads on our server and imagekit will do all our media heavy lifting. I chose these tools because I just found them easier to use and the latter has a very elaborate documentation (and a free tier too 😋). - Source: dev.to / over 1 year 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.
Cloudinary - Cloudinary is a cloud-based service for hosting videos and images designed specifically with the needs of web and mobile developers in mind.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
imgix - Real-time Image Processing. Resize, crop, and process images on the fly, simply by changing their URLs.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Cloudimage - Cloudimage.io is the easiest way to resize, store, and deliver your images to your customers through a rocket fast CDN.