Why TensorFlow?

[MUSIC PLAYING] SPEAKER: TensorFlow is an open source end-to-end platform for machine learning. It provides a comprehensive ecosystem of tools for developers, enterprises, and researchers who want to push the state-of-the-art of machine learning and build scalable machine learning-powered applications. TensorFlow was designed to help you learn to build models easily. With an intuitive easy-to-use set of APIs that makes it simple for you to learn and implement machine learning, deep learning, and scientific computing, it provides you with a rich collection of tools for building models. These include data pre-processing, data ingestion, model evaluation, visualization, and serving. But it's not just for building models. You can easily train and deploy your model anywhere with TensorFlow. It's designed to be highly portable, running on a variety of devices and platforms. It can scale from a single CPU to a GPU or cluster of GPUs, all the way up to a multi-node TPU infrastructure. So it's simple to build models that work on any platform taking advantage of the power of each. TensorFlow also allows for powerful experimentation. With the flexibility to quickly implement state-of-the-art models, TensorFlow can power your research into new techniques to solve novel problems, these include diagnosis of diabetic retinopathy, helping rural farmers spot diseased plants, and predicting extreme weather conditions with fast debugging and the ability to apply state of the art ML models. And to top it all off, TensorFlow is driven by a worldwide community. This community is open and diverse. TensorFlow derives its roadmap from the needs of its users with a vision to provide a machine learning platform that's for everyone. You can learn more about TensorFlow at TensorFlow.org.

Channel: TensorFlow

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Id: yjprpOoH5c8

Length: 2min 22sec (142 seconds)

Published: Wed Jul 15 2020