TensorFlow
This is a talk for people who know code, but who don’t necessarily know machine learning. Learn the ‘new’ paradigm of machine learning, and how models are an alternative implementation for some logic scenarios, as opposed to writing if/then rules and other code. This session will guide you through understanding many of the new concepts in machine learning that you might not be familiar with including eager mode, training loops, optimizers, and loss functions.
Watch more #io19 here: Machine Learning at Google I/O 2019 Playlist → https://goo.gle/2URpjol
TensorFlow at Google I/O 2019 Playlist → http://bit.ly/2GW7ZJM
Google I/O 2019 All Sessions Playlist → https://goo.gle/io19allsessions
Learn more on the I/O Website → https://google.com/io
Subscribe to the TensorFlow Channel → https://bit.ly/TensorFlow1
Get started at → https://www.tensorflow.org/
Speaker(s): Laurence Moroney and Karmel Allison
T700B4
Source
Unrelated. But I was in the hospital as my baby daughter was being born as this event was occurring 🙂
Wow
Very enlightening talk.
How long an ML noob like me who is rather experienced Android Kotlin dev would take to create a similar image recognizer app?
I'm not understanding why the 150×150 image be omes 148×148.
God ! That screen ❤️.
amazing, this is pure genius, if you want to learn more, look for tensor flow coarse on coursera
Why 512 in the 2nd line of the model code? How do I decide on this number? How to decide on loss and optimizer?
Imagine using this amphitheater for a rock concert!
anyhow Im now switching from pytorch to tensorflow
I need the right code
This was just amazing
Really enjoyed the cat speech !
good
good
@laurence Moroney Can you please share complete code with us ? You are very good professor . Which course on Coursera that you teach to enroll later ?
In collage, i learn about Fuzzy Logic, the program neural network in this video is like perceptron. Am i right?
This is excellent! this demonstrates how ML is just a more advanced version of software and not some magical energy that will become an overlord but more importantly gives us the foundation to learn the essential to get into building apps with TensorFlow
This is the best artificial intelligence video available. Great explanation. Thank you Google Team.
Thanks for the quality presentation! Really helps understand the process behind TF
Does anyone have a simple weblink to the slides and source repo? Thanks
Love it ml…. ❤️❤️❤️❤️❤️
Thanks
Second part is really bad commercial
I like it! Super! Keep Going!
Very good explanation of lots of thing about machine learning
Nailed it
Don’t be surprise when youtube becomes better than schools, and colleges.
had seen your nlp intro vid that was brilliant loved this one to
This is great. I wanna start something in ML. Thanks for sharing
This is one of the best video on machine learning
This is great. I wanna start something in ML. Thanks for sharing
This is the best tutorial/introduction that I have ever watched
what a man !! i am a surgeon and hardly know how to open the computer and i understand what he did say !!
Thanks
Why not use shaders for convolution and feed it a direct convoluted image stream of everything it see's (ALREADY CONVOLUTED) instead of picking things out that are convoluted individually?
It would speed up the process FAR MORE…
This is one of the best video on machine learning
This is amazing!!!!
This is amazing!!!!
This is the best tutorial/introduction that I have ever watched
Nice explanation. Thoroughly enjoyed the presentation 🙂
This is the best tutorial/introduction that I have ever watched
The best explanation of convolution in few minutes.
🙏
Nice explanation. Thoroughly enjoyed the presentation 🙂
What I am curious about is why some code is CamalCase and others underscore?
Wonderfully and beautifully explained introduction video!
This is one of the best video on machine learning
The best explanation of convolution in few minutes.
🙏
So simply explained, this is amazing, thank you
18:10 top-right corner :3
This is the best artificial intelligence video available. Great explanation. Thank you Google Team.
This is one of the best video on machine learning