ML model Inference flow

In Most of the scenarios, ML/DL (Machine Learning/ Deep Learning) solutions in production use Tensorflow to build their product. Because Tensorflow(TF) has extensive production community support when compared to PyTorch.(However, PyTorch is a go-to choice for ML/DL researchers due to its flexibility)

So let me explain how the data preprocessing should be done:

  1. Always decouple data Preprocessing component from Model Training/Inferencing Component.
  2. Use tf.Transform for Preprocessing

I will get back to why tf.Transform ?

1. why do we need to decouple the data preprocessing component from other components in the ML pipeline.?

What is pre-processing in the context of ML ?

“A process of converting raw inputs to features to train the machine learning model”

When you are…

Surya Bandlamudi

Machine Learning Engineer

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