The Spot Challenge for CodeNet continues  with a session where we'll answer questions and cover specialized topics related to the challenge that are of interest to the session attendees and challenge contestants.

Hear from Maleeha Koul (Data Scientist) & Shankara Narayanan (Data and AI Solutions Specialist) on their experiences so far trying out the samples and starter code from the CodeNet Code Similarity Challenge e.g.,

https://github.com/IBM/Project_CodeNet/tree/main/Contest/ExampleSimAnalysis

We'll also summarize all the resources available so far for the challenge

Bring your questions for discussion by our data scientist researchers as we continue to guide teams participating in the challenge using an extract from Project CodeNet.

Catch up on previous sessions in this series

- Introductory to the CodeNet Call for Code Challenge Session https://www.crowdcast.io/e/call-for-code-spot-9

- Call for Spot Challenge for CodeNet - Setting up your system for the challenge  https://www.crowdcast.io/e/call-for-spot-challenge

- Spot Challenge for CodeNet - Graph Neural Network Techniques for Code Similarity  https://www.crowdcast.io/e/spot-challenge-for

-Transformers for Larger Data Sets & Experiences in CodeNet Contest Leaderboard   https://www.crowdcast.io/e/spot-challenge-for-2

- Spot Challenge for CodeNet and High Performance Deep Learning https://www.crowdcast.io/e/spot-challenge-for-3

Our final session is December 26 @ 10:00am CST

https://developer.ibm.com/events/spot-challenge-for-codenet

Spot Challenge for CodeNet - Experiences getting started with the CodeNet Code Similarity Challenge