Machine learning models + IoT data = a smarter world (Google I/O '18)
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- Опубликовано: 18 окт 2024
- With the IoT market set to triple in size by 2020, 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.
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Watch more IoT sessions from I/O '18 here → goo.gl/xfowJ8
See all the sessions from Google I/O '18 here → goo.gl/q1Tr8x
Subscribe to the Google Developers channel → goo.gl/mQyv5L
#io18 event: Google I/O 2018; re_ty: Publish; product: Cloud - Internet of Things (IoT) - IoT Core, Cloud - Data Analytics - PubSub, Cloud - Containers - Google Kubernetes Engine (GKE), TensorFlow - General, Cloud - AI and Machine Learning - AI Platform; fullname: Laurence Moroney, Kaz Sato; event: Google I/O 2018;
Hi, I come from an Electronics and Telecommunication background with 10 years of Telecom Domain experience , and at present trying to find my way to full time Machine Learning Engineer + IOT Engineer. To me i always look from a end product perspective , something can be commercialized so that people can benefit from it. Your talk gave me real time use of how DS+MS+ML+DL+IOT can be used in real time . I am looking for more use cases , something I can try on my own. So thank you again for your time making this video, it was really insightful to the real world of AI in the future.
Any resources you can recommend?
hello can i have your email i need your help in my research area
By counting of the number of views and the number of comments, I can. Say that only few people are actually love to develop the things or in simple words the creators while all others are just the customers.
Hope future is bright 👍
Awesome presentation sir.
If I were you I would count the top talents as the people who went in-person for the i/o
Only a few understand how the future will work and also want the changes.
Very interesting ML and IoT talk. Really excited to try out the links referenced. Speakers and demos were really inspirational 👏🏼
Thanks Graham! :)
Thank you so much to both of you and the team.
Explained in a very simple way and was easily able to connect. Looking forward to build the demo projects soon.
Enjoyable and informative talk. Thanks for this.
THanks for the feedback! :)
Excellent, really cool,I got inspired, don't know y these videos deserve r not getting lot f views... great talk
Thanks for sharing! Neat combination between ML and IoT
Thanks Dat! :)
is arduino + the cheap AQ sensor reliable enough for a commercial implementation ?
Grateful for this video. But the first sensor shown is definitely not an air quality sensor. Just a simple CO2 sensor. Imo a solid small and reliable air quality sensor does not yet exist. Honestly that first demo is kinda a sham.
Exciting times
nice video I am interested in this field
That's Awesome
thanks (y)
I love it
This is a great video. A friend and I worked on a similar idea in grad school (ruclips.net/video/YuS6B1hL_h8/видео.html) and so inspiring to see that its real world application are no far away.
shopping cat🐱