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There are various forms for metadata that datasets use...To get access to the WOC, send email to weatheroperations@us.ibm.com i ndicating that you are a Call for Code participant
The contest is over - Thank you for your contributions Many Congratulations: Team Abiret See Linked In Post As preparation for competing in the challenge we ran these crowdcast sessions: Introduction to the Challenge: https://www.crowdcast.io/e/call-for-code-spot-9 Setting up your system: https://www.crowdcast.io/e/call-for-spot-challenge Learn about 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 Experiences getting started with the CodeNet Code Similarity Challenge: https://www.crowdcast.io/e/spot-challenge-for-code Final Contest dataset https://www.crowdcast.io/e/spot-challenge-for-4 Summary I ncreasingly software plays a role in every aspect of our lives, from managing Covid-19 and our finances, to interacting with other humans in education, work, and entertainment
News Read a blog that summarizes resources derived from the Wildfires Challenge Apr 21, 2021 https://dev.to/ibmdeveloper/a-summary-of-resources-for-wildfires-for-call-for-code-2h93 Hear a Comparison of Model Approaches Apr 5, 2021 https://www.crowdcast.io/e/predicting-australian Crowdcast-Wildfires-2021-04-05-f-Susan-Assembled-Slides.pdf Read about a Comparison of Model Approaches Mar 25, 2021 https://developer.ibm.com/technologies/artificial-intelligence/blogs/call-for-code-spot-challenge-for-wildfires-predictions-comparing-approaches/ The Final Results Posted on the Leaderboard Mar 2 , 2021 The Finale - and Next Steps Hear from IBMers building models for the wildfires challenge Feb 22, 2021 - https://www.crowdcast.io/e/call-for-code-spot-7 A Summary of Self Study Materials is Available Jan 26, 2021 - You can find a list of self-study materials here The Evaluation Script is Now Public Jan 16, 2021 - You can find the challenge evaluation script here https://github.com/Call-for-Code/Spot-Challenge-Wildfires/tree/main/evaluation scripts and if you consult the readme you can run it yourself
Well , that's where AI for Code comes into the picture [1]. In recent years, a fast-growing discipline called AI for Code aims to help software engineers improve their productivity by automating the code developing process, such as code auto-complete, natural language to code auto-translation, code debugging, etc
Project CodeNet provides a rich dataset, consisting of 14 million code samples and 500 million lines of code in 55+ programming languages, along with tools aimed at advancing research in AI for code