Learn more: Mesh TensorFlow → goo.gle/3sFPrHw Distributed Training with Keras tutorial → goo.gle/3FE6QEa GCP Reduction Server Blog → goo.gle/3EEznYB Multi Worker Mirrored Strategy tutorial → goo.gle/3JkQT7Y Parameter Server Strategy tutorial → goo.gle/2Zz3UrW Distributed training on GCP Demo → goo.gle/3pABNDE
Assalamualaikum She is a Mushrik wearing Graven images on necklace and worshipping man made false idols. She is Breaking the 1st Commandment in Deuteronomy Chapter 5 verses 7-9
Learn more:
Mesh TensorFlow → goo.gle/3sFPrHw
Distributed Training with Keras tutorial → goo.gle/3FE6QEa
GCP Reduction Server Blog → goo.gle/3EEznYB
Multi Worker Mirrored Strategy tutorial → goo.gle/3JkQT7Y
Parameter Server Strategy tutorial → goo.gle/2Zz3UrW
Distributed training on GCP Demo → goo.gle/3pABNDE
Assalamualaikum
She is a Mushrik wearing Graven images on necklace and worshipping man made false idols.
She is Breaking the 1st Commandment in Deuteronomy Chapter 5 verses 7-9
Wow Ring All-Reduce is just... beautiful. 😍
this is really well explained. more on this series please. thanks
Correction: At 14:37, there is no C4 in GPU-1. It should be C2.
awesome video, crystal clear with the content design and easy to understand
Well done. I hop to see more videos.
Thank you very much for the insightful presentation.
Good an easy to understand explanations!
At time code 15:23 in the Ring Reduce algorithm the subscripts for the c vector are incorrect.
there is a bomb hidden in the algorithm LOL
Awsm and easy to understand.
Straightforward and awesome
What if i dont have gpus as you said in the video, i have 32 systems with i5 CPU..can i run this mirrored strategy on multiple CPUs?
Great content. Look forward to more.
Thank you! Want to watch more? Check out this playlist, ML Tech Talks → goo.gle/ml-tech-talks
GPU must be same, what happens if i use different GPU???
nicely done!
Nicely explained!
Hello is there any docs about federated learning with differentiel privacy, thank you
wow, great job!
Amazing!!
Thank you
Thank
thanks
That tf.distribute.experimental worries me.. not sure when the api will be deprecated.
Thanks