Join this meetup and network with Machine Learning developers from around the world. During the meetup, we'll discuss the latest features, learn from Google’s experts, share experiences and interests, and find opportunities to collaborate with other ML developers.
Lighting Talk #1
- Title: Monitoring 3D Printers with Computer Vision
- Speaker: Leigh Johnson (ML GDE)
- Brief: Technical deep dive into how I built Print Nanny, which automatically detects 3D print failures with a Raspberry Pi. I’ll cover each phase of development, from prototype to meeting customer demand at scale.
Lighting Talk #2
- Title: Launching the ML GDEs YouTube Channel
- Speaker: Margaret Maynard-Reid (ML GDE)
- Brief: How the ML GDEs collaborated with each other to create unique content and share our knowledge via YouTube videos: from story-telling intros, tech talks to fun interviews (in various languages). Join this talk to learn about creative community collaboration, tips on how to record videos, and great learning resources of AI/ML from the experts.
- Title: Awesome TensorFlow Lite
- Speaker: Margaret Maynard-Reido (ML GDE)
- Brief: Join this talk to learn about TensorFlow Lite project collaboration by ML GDEs, Googlers and the community. Fun project and app showcases and demos. Various learning resources from our awesome TensorFlow Lite community.
Lighting Talk #3
- Title: Elegy: A next-gen framework
- Speaker: David Cardozo (ML GDE)
- Brief: Elegy: A framework-agnostic trainer interface for the JAX ecosystem
Lighting Talk #4
- Title: How to integrate Responsible AI practices into your ML workflow using TensorFlow
- Speaker: Vinicius Caridá (ML GDE)
- Brief: Responsible AI tools for TensorFlow and key questions to consider at each step of the ML workflow
Lighting Talk #5
- Title: How to deal with Unbalanced Image Datasets in less than 20 lines of code
- Speaker: Arnaldo Gualberto (ML GDE)
- Brief: In this talk, we're going to see how to write a custom Dataset Generator in TensorFlow to deal with unbalanced datasets.
Lighting Talk #6
- Title: Landmark Detection using TensorFlow Hub
- Speaker: Bhavesh Bhatt (ML GDE)
- Brief: This talk will present how you can use the pre-trained models on TF Hub to create unique applications. I'll showcase one such application of using a pretrained model from Tensorflow Hub that is to detect landmarks in different continents.