Distributed Deep Learning Made Easy

This is a guest post from my colleagues Naveen Swamy and Joseph Spisak.——————————— Machine learning is a field of computer science that enables computers to learn without being explicitly programmed. It focuses on algorithms that can learn from and make predictions on data. Most recently, one branch of machine learning, called deep learning, has been deployed successfully in production with higher accuracy than traditional techniques, enabling capabilities such as speech recognition, image recognition, and video analytics. This higher accuracy comes, however, at the cost of significantly higher compute requirements for training these deep models. One of the major reasons for this rebirth and rapid progress is the availability and democratization of cloud-scale computing. Training state-of-the-art deep neural networks can be time-consuming, with larger networks like ResidualNet taking several days to…


Link to Full Article: Distributed Deep Learning Made Easy

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