An end-to-end open source machine learning platform
Build and train deep learning models easily with high-level APIs like Keras and TF Datasets.
Iterate rapidly and debug easily with eager execution.
Scale computations to accelerators like GPUs, TPUs, and clusters with graph execution.
Deploy models to the cloud, on-prem, in the browser, or on-device.
A comprehensive ecosystem of tools, libraries and community resources that lets beginners quickly get started, researchers push the state-of-the-art in ML, and engineers easily build and deploy ML powered applications.
Examples demonstrate focused applications of deep learning workflows.
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The Deep Learning with R book shows you how to get started with Tensorflow and Keras in R, even if you have no background in mathematics or data science. The book covers:
Deep learning from first principles
Image classification and image segmentation
Time series forecasting
Text classification and machine translation
Text generation, neural style transfer, and image generation