Different people learn different things in different ways. Some people learn by listening to lectures and teachers, some by reading and self-study, and some by either doing or trying out things for themselves or in an apprenticeship sort of a setting.

Children mostly learn by either listening or doing things…


Amazon.com swears by “Working Backwards” as a tenet. And it is an excellent tenet that has worked well for the company. The work culture is such that even all of its employees adhere to it as a principle.

Working at Amazon, I, too, got to learn the benefits of this…


I recently watched this talk by Zachary Lipton. The talk is two years old but still relevant, important, and informative.

Here are few things that stuck out for me on this matter -

  • Excitement + Ignorance = Misinformation
  • AI/ML is currently in the same phase that the dot com boom…


In many Machine Learning or Data Science workflows, it is common to save and checkpoint several models and compare how they perform on a held-out validation dataset. These saved models could be -

  • checkpoints in a single training trial saved at different time epochs, in which case the network structure…


In this post, I will share a few of my thoughts on explainability in AI/ML.

Motivating Stories

These situations ought to explain why explainability in AI is important.

  • When a human is riding a self-driving taxi, and the taxi takes a sudden unexpected detour, you become suspicious and probably scared, wondering if…


Authors: Anirudh Acharya, Rajan Singh , Roshani Nagmote, Hagay Lupesko — Amazon AI software engineers.

MXNet 1.2 adds built-in support for ONNX

With the latest Apache MXNet 1.2 release, MXNet users can now use a built-in API to import ONNX models into MXNet. …

Anirudh Acharya

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