Learn how to seamlessly develop an open source data science stack by combining the compact syntax of Python with the flexibility of a schema-less graph database. Most data scientists will tell you that they spend the majority of their time cleaning and munging data and only a fraction of their time actually building predictive models. This session will show you how to use Python to collect data from Twitter’s API, Neo4j to easily and reliably store this highly-connected data, and Python again for quick analysis and visualization.
Read more about it here: https://development.neo4j.dev/blog/building-python-web-application-using-flask-neo4j/
#Python #Neo4j #DataScience