Note: To participate in PyCon India, please ensure you purchase your tickets directly from KonfHub (https://konfhub.com/pyconindia2023#tickets). RSVP on this meetup registration will not grant access to PyCon India.
Trying to find the optimal route through a crowded theme park? Model it as a graph! In this talk, we’ll build a theme park mobile app and use Neo4j’s graph algorithms to find the fastest way between rides, shows, and restaurants. You’ll learn how to model real-world data as nodes and relationships, replacing hierarchical models and if-then logic with graph traversals.
Hear Jason and Alison dive into common graph theory concepts like nodes, edges, paths, and more. See how to translate business objects into a property graph schema and write efficient Python code using Neo4j’s graph algorithms. Traverse relationships to find paths, recommend connections, and surface insights without complex joins.
Graph databases shine for interconnected data and when requirements evolve. We’ll demo querying and traversing a graph from our Python application, focusing on the power of connections over rigid schemas. You’ll walk away ready for the flexibility and convenience of graph databases in your own projects.
Topic: Efficiency through Simplicity: Avoiding if-then statements with graphs
Speakers:
🎤Jason Koo, Developer Advocacy Manager @ Neo4j
Bio:
Mobile Developer turned Pythonista, Jason Koo is a Developer Advocate Manager at Neo4j focused on supporting the Python community and a small but mighty team of Technical Advocates. He regularly speaks at developer meetups and conferences up and down the US West Coast. He also organizes and hosts a thriving Graph Database Meetup group in his hometown of sunny San Diego.
🎤Alison Cossette, Data Science Advocate @ Neo4j
Bio:
Alison Cossette is a Graph Data Science Advocate at Neo4j with over 10 years of experience applying graph analytics and machine learning to generate business insights. She founded ExplainIt.ai to advocate for responsible AI solutions and empower data-driven decisions through education. An educator and thought leader, she has taught hundreds of aspiring data scientists and shares her passion for graph data science and responsible AI through speaking and podcasts.
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