Mastering AI: Big Data, Deep Learning, and the Evolution of Large Language Models -- AutoML from Basics to State-of-the-Art Techniques

Pohsun Feng; Ziqian Bi; Yizhu Wen; Benji Peng; Junyu Liu; Caitlyn Heqi Yin; Tianyang Wang; Keyu Chen; Sen Zhang; Ming Li; Jiawei Xu; Ming Liu; Xuanhe Pan; Jinlang Wang; Xinyuan Song; Qian Niu

arXiv · 2410.09596

Mastering AI: Big Data, Deep Learning, and the Evolution of Large Language Models -- AutoML from Basics to State-of-the-Art Techniques

Pohsun Feng·Ziqian Bi·Yizhu Wen·Benji Peng·Junyu Liu·Caitlyn Heqi Yin·Tianyang Wang·Keyu Chen·Sen Zhang·Ming Li·Jiawei Xu·Ming Liu·Xuanhe Pan·Jinlang Wang·Xinyuan Song·Qian Niu

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Abstract

A comprehensive guide to Automated Machine Learning (AutoML) is presented, covering fundamental principles, practical implementations, and future trends. The paper is structured to assist both beginners and experienced practitioners, with detailed discussions on popular AutoML tools such as TPOT, AutoGluon, and Auto-Keras. Emerging topics like Neural Architecture Search (NAS) and AutoML's applications in deep learning are also addressed. It is anticipated that this work will contribute to ongoing research and development in the field of AI and machine learning.

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Pohsun Feng, Ziqian Bi, Yizhu Wen, Benji Peng, Junyu Liu, Caitlyn Heqi Yin, Tianyang Wang, Keyu Chen, Sen Zhang, Ming Li, Jiawei Xu, Ming Liu, Xuanhe Pan, Jinlang Wang, Xinyuan Song, Qian Niu. 2025-12-07. Mastering AI: Big Data, Deep Learning, and the Evolution of Large Language Models -- AutoML from Basics to State-of-the-Art Techniques. https://arxiv.org/abs/2410.09596

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