Kaggle Grandmaster Chris Deotte, he is currently ranked 1 on notebooks and discussions on Kaggle and is part of the KGMON team, Kaggle Grandmasters of NVIDIA. We’ll be discussing GEN AI and personalization, optimizing your kaggle game and other strategies to make progress in your career.
Solution: https://arxiv.org/pdf/2408.04658
Mark Moyou, PhD Socials:
LinkedIn: https://www.linkedin.com/in/markmoyou/
Twitter: https://twitter.com/MarkMoyou
Chapters:
00:00 Intro
01:51 Current Gen AI
04:40 Evolution of Conceptualization in ML Models
06:59 Measuring Tonality in Data Sets
08:51 Multi-Modal Data Sets in Text Based Models
11:56 Large Vs Small Language Models
13:46 KDD 2024 Competition
23:28 Prompt Formatting and Bribing the Model
28:08 Qwen2 Vs LLama
30:39 WiSE - FT
33:53 LoRA on all the layers
35:43 Logit Preprocessor
42:05 Personality of Small Vs Large Model
44:02 Models Understanding Shopping Concepts for E-Commerce
47:26 Offline Purchase Data in E-Commerce Personalization
55:56 Navigating the Problem with Required Data
58:33 Constraining LLM Output
01:00:45 LLMs in Search and Personalization
01:02:03 Kaggle Grandmaster
01:09:45 Gen AI in Kaggle Competition
01:13:07 Learning ML in Non-Traditional Way
01:16:15 Thoughts on doing PhD
01:17:58 Mathematics
01:22:22 Advice for PhD students
01:24:32 Hardest Kaggle Competition
01:27:32 Level of Grit in Competitions
01:32:59 Career Optimization Function
01:35:00 Management vs Technical IC Roles
01:37:27 Making Progress
01:39:48 Book Recommendations
01:44:43 Thoughts on Writing Book
01:46:20 Advice for High Schooler, College Students and Professionals
01:52:20 Rapid Round
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