Deep learning for Android with TensorFlow
Who is this presentation for?
- ML engineers and AI researchers who would like to deploy models to Android
If you’re interested in making intelligent apps with the most popular deep learning framework, TensorFlow, join Margaret Maynard-Reid to learn your various options from using ready-made APIs to training your own custom models. You’ll learn the end-to-end process of how to train a model with TensorFlow high-level API tf.Keras, convert it to a TensorFlow Lite model, and deploy it to Android.
You’ll get an introduction to tf.Keras and TensorFlow Lite; learn how to integrate ML Kit, a Mobile SDK powered by TensorFlow Lite; transfer learning with a pretrained model (using tf.Keras or TensorFlow Hub); and train a model from scratch and deploy it to Android for inference.
- A basic understanding of TensorFlow and deep learning (useful but not required)
What you'll learn
- Get an introduction to TensorFlow, TensorFlow Lite, and ML Kit
- Learn how to integrate ML Kit, a Mobile SDK powered by TensorFlow Lite; transfer learning with a pretrained model (using tf.Keras or TensorFlow Hub); and train a model from scratch and deploy it to Android for inference
Margaret Maynard-Reid is a machine learning engineer and Google Developer Expert (GDE) at Tiny Peppers, and she’s a contributor to the open source ML framework TensorFlow. She writes blog posts and speaks at conferences about on-device ML, deep learning, computer vision, TensorFlow, and Android. Margaret is passionate about community building and helping others get started with AI and ML. She’s a community leader of GDG Seattle and Seattle Data/Analytics/Machine Learning Meetup.
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