AI Recommendation System with TensorFlow

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.