Whether you are counting cars on a road or people stranded on rooftops in a natural disaster, there are plenty of use cases for object detection. Often times, pre-trained object detection models do not suit our needs and we need to create our own custom models.
How can we utilize machine learning to train our own custom model without substantive computing power and time?
Answer: Watson Machine Learning.
How can we leverage our custom trained model to detect object’s, in real-time, with complete user privacy, all in the browser?
In this workshop, you will create a web app that does just that. You will learn how to create an IBM Cloud Object Storage instance to store your labeled data. Once your data is ready, you will learn how to spin up a Watson Machine Learning instance to train your own custom model on top-of-the-line GPUs. After your model has completed training, you can simply plug the TensorFlow.js model into your react application.
At the end of this workshop, you should understand how to:
- Label data that can be used for object detection
- Use your custom data to train a model using Watson Machine Learning
- Detect objects with TensorFlow.js in the browser
Install Node.js v10 or above https://nodejs.org/en/download/
Get a head start and join IBM Cloud via: https://ibm.biz/BdzczH
- 6:30-7pm - Doors Open for Networking & Food
- 7-845pm - Hands-On Workshop
- 9pm - Venue closes
About the Presenters
Mofizur Rahman (@moficodes) is a Developer Advocate at IBM Cloud. His area of interests include container orchestration, micro services and blockchain. His favorite programming language these days is Go. He also tinkers with Node, Python and Java. He is also learning and teaching in the Go, Kubernetes and Hyperledger Fabric community. He is a strong believer of the power open source and importance of giving back to the community. He is a self proclaimed sticker collecting addict and has collected several box full of stickers with no signs of stopping. He dabbles in photography sometimes.
He writes tech blogs at NYCDEV medium page which can be found on https://medium.com/@moficodes