Guide to Building Recommendation System with Tensorflow

  • Recommendation System with Tensorflow builds a recommendation engine capable of learning from specific positive and negative feedback, allowing for arbitrary TensorFlow graphs used as representation functions and loss functions.
  • It provides reasonable defaults for representation functions and loss functions. It packs as many Machine Learning buzzwords into a Medium post as possible.
  • TensorFlow, initially developed by Google, is an open source tool that to build, optimize, and distribute large, arbitrary Machine Learning system.
  • Machine Learning process expressed as a ‘graph’ showing data flow through the system, graphs visualized using TensorBoard.

Steps to build Recommendation System using Tensorflow –

  • Transform input data into feature tensors for easy embedding.
  • Transform user feature tensors into user representations function.
  • Transform a pair of representations into a prediction.
  • Transform predictions and truth values into a loss value function.