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Deep Learning Platforms
TensorFlow
Initially created by Google Brain’s Machine Intelligence team, TensorFlow was designed for machine learning and neural network research. This flexible, scalable system works on various platforms using different accelerators, such as GPUs, NPUs, and TPUs. It provides robust support for the training and development of generative adversarial networks (GANs). These sophisticated neural network architectures consist of two competing models: a generator that creates synt
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Keras
Keras is a high-level neural network library written in Python that runs on top of TensorFlow, Microsoft Cognitive Toolkit, Theano, or PlaidML. It was designed to enable fast experimentation with deep neural networks. Keras began as a library offering a wide range of abstractions to simplify interactions with neural networks. Initially, it supported multiple backends, including TensorFlow, Mi
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PyTorch
PyTorch is an open-source machine learning library developed by Facebook's AI Research lab. It's primarily used for deep learning and artificial intelligence applications.
Read Guides about PyTorch
PaddlePaddle
PaddlePaddle, created by China’s largest search engine Baidu, is positioned as a more user-friendly alternative to DSSTNE (Amazon), TensorFlow (Google), and CNTK (Microsoft). It’s an R&D platform focused on neural networks. In its eight-year history, PaddlePaddle has attracted over 4 million developers, with more than 157,000 companies using products developed through its platform. In today’s world, open source softw
Read Guides about PaddlePaddle
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