Introduction to Distributed Deep Learnring

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In this video you will learn the concepts and architectures available to train Deep Learning models across multiple machines.You will learn why distributed deep learning is becoming relevant, what are the strategies available in TensorFlow, where they come from, and which one to use.
  1. mlverse
  2. Distributed Deep Learning
  3. Deep Learning
  4. Distributed Computing
  5. TensorFlow
  6. Spark
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Комментарии
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Thanks for the video and also for discussing relevant papers, tried benefits and issues that arise with each strategy. In terms of the use of the terminology "distributed", I do agree that it should refer to more than one computer.

jeromeeusebius
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Excellent introduction/overview. Thank you!

brandonmckinzie
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Thanks a lot for sharing, definitely it would prove to be a guide for me to proceed.

sandeepgill
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This video is awesome and gave lot of information. Hopefully i will be able to make use of this information in my project. If there is any free source where i could use multiple GPU please help me with it. I'm still a student working on a college project. I need a multiple machines to train the model my dataset is hug any advice will be helpful.

abhishekgupta-lhys
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Thanks. Although, this is a lot of IT c**p that annoys me as a researcher when the relevant topic should be more about econometrics, statistics and algorithms.

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