TensorFlow makes it easy to create ML models that can run in any environment. Learn how to use the intuitive APIs through interactive code samples.
Developers who are looking to experiment and bring their ideas to life fast.
Developers looking for a flexible and intuitive platform for deep learning models.
PyTensor is a Python library that allows you to define, optimize/rewrite, and evaluate mathematical expressions involving multi-dimensional arrays efficiently.
fastai is a deep learning library which provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains, and provides researchers with low-level components that can be mixed and matched to build new approaches.
PyTorch Lightning offers a high-level interface for PyTorch. Its high-performance and lightweight framework can organize PyTorch code to decouple the research from the engineering, making deep learning experiments simpler to understand and reproduce. It was developed to create scalable deep learning models that can seamlessly run on distributed hardware.
Built on Keras and Apache Spark, Dist-Keras focuses on distributed deep learning.
Developed by BVLC and BAIR, Caffe specializes in vision-based machine learning tasks. It excels in image classification and convolutional neural networks.
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