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  1. Running large scale inference jobs
  2. Pre-processing input data — and materializing it on disk as
    preparation for training

Optimize your deep learning training process by understanding and tuning data loading from disk to GPU memory

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Why you should read this post

Why ML needs its own flavour of dev. methodology and a partial, draft proposal for such a methodology

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  • ML teams working on complex projects need to battle the intrinsic challenges in ML, as well as the friction which arises from their multi-disciplinary nature which makes it hard to make decisions.
    A solid Development Methodology can help teams improve execution.
  • ML is different from standard software in its level…

Assaf Pinhasi

Machine Learning and Engineering Leader and consultant.

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