The Good, Bad, & Ugly of TensorFlow

  • If you are deploying a model to a cloud environment, you want to know that your model can execute on the hardware available to it, without unpredictable interactions with other code that may access the same hardware.
  • For me, holding mental context for a new framework and model I’m building to solve a hard problem is already pretty taxing, so it can be really helpful to inspect a totally different representation of a model; the TensorBoard graph visualization is great for this.
  • For example, the Udacity tutorials and the RNN tutorial using Penn TreeBank data to build a language model are very illustrative, thanks to their simplicity.

Read the full article, click here.


@rasbt: “The Good, Bad, & Ugly of TensorFlow – survey of 6 months rapid evolution (+ tips/hacks & code to fix the ugly stuff)”


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The Good, Bad, & Ugly of TensorFlow