Recommendations with IBM
Overview
An important part on IBM Watson Studio is the community; it's a collaborative ecosystem of curated datasets, articles, notebooks or other kinds of assets that are out there in the world of data science, machine learning and artificial intelligence. The data is the anonymized data of the interactions between all of the different kinds of articles, datasets etc available. The users interact with these assets on the platform.
The task is to build a personalized recommendation system for these assets in the community, and provide that presonalized recommendation experience with a web app.
Tasks
Exploratory Data Analysis
Rank Based Recommendations
User-User Based Collaborative Filtering
Content Based Recommendations
Matrix Factorization
Libraries
- numpy
- pandas
- matplotlib