Introduction to Machine Learning with TensorFlow (Presentation and Codelab)
During this session, we will discuss how ML is different to traditional programming. Audience will have a chance to develop a neural network with Tensorflow using the Keras API
12:00pm - 1:00pm
Build a digit classifier app with TF Lite (Presentation and Codelab)
You will be presented with an introduction to Tensorflow Lite and Tensorflow Lite Workflow and proceed with working through a codelab. At the end of this session, you will have a firm understanding of why on-device Machine Learning is important.
1:00pm - 2:00pm
2:00pm - 3:00pm
Recognize Flowers with TensorFlow Lite on Android (Codelab)
We will be discussing what is transfer learning by working with the model customization toolkit (aka. Model Maker) and the TF Lite support library for Android.
3:00pm - 3:30pm
TF Lite pretrained models and reference apps (Presentation)
This session presents multiple pre-trained models that are ready to use in TF Lite and ML Kit.
3:30pm - 4:00pm
Introduction to ML Kit (Presentation)
We will switch gears from TF Lite to discuss ML Kit, a Firebase product for developers to build ML powered apps.
4:00pm - 4:15pm
4:15pm - 5:15pm
ML Kit codelab(Codelab)
Putting our understanding to practice, you will get a chance to go through an ML Kit codelab to learn how to develop with ML Kit.
5:15pm - 5:45pm
Introduction to Cloud AI(Presentation)
Lastly, you will be introduce to a slew of Machine Learning products on the Google Cloud Platform. You will have a chance to better understand how to leverage the scaling nature of cloud to train models with large datasets at scale, etc.
5:45pm - 6:15pm
Train a salad detector with Cloud AutoML Vision Edge(Codelab)
In the last codelab of the day, you will be working on a codelab to build a salad detector with Cloud AutoML and Vision Edge API.
6:15pm - 6:30pm
*Please note, the above agenda is subject to change.