With the IoT market set to triple in size by 2023, and massive increases in computing power on small devices, the intersection of IoT and machine learning is a trend that all developers should pay attention to. This talk will cover three core use cases, including: how to manage sourcing data from IoT devices to drive machine-learned models; how to deploy and use trained models on mobile devices; and how to do on-device training with a Raspberry Pi computer.
Rate this session by signing-in on the I/O website here → https://goo.gl/rYcGev
Watch more IoT sessions from I/O ’18 here → https://goo.gl/xfowJ8
See all the sessions from Google I/O ’18 here → https://goo.gl/q1Tr8x
Subscribe to the Google Developers channel → http://goo.gl/mQyv5L
#io18
Related Post:
- Machine learning models + IoT data = a smarter world (Google I/O ’18)
- Smart Cash Review – Smarter Cryptocurrency for a Smarter Future
- Smarter Data Management! – CryptoCurrency Data Management – Essentia Crypto ICO Review
- What’s New in Google’s IoT Platform? Ubiquitous Computing at Google (Google I/O ’17)
- The Future of IoT and Machine to Machine Payments
- TechConnect: Tech Powered Sports with IoT & Machine Learning
- Scott Hanselman’s best demo! IoT, Azure, Machine Learning & more
- IoT and Machine Learning – Changing the Future | Dr. Dennis Ong | TEDxOhioStateUniversity
- THE BIG STORY: SIA bans some models of Macbook Pro | NRIC data collection rules
- mPrest & Netafim: Smarter Irrigation with AWS IoT Core