Summary of Mastering Ai: Big Data, Deep Learning, and the Evolution Of Large Language Models — Automl From Basics to State-of-the-art Techniques, by Pohsun Feng et al.
Mastering AI: Big Data, Deep Learning, and the Evolution of Large Language Models – AutoML from Basics to State-of-the-Art Techniques
by 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, Qian Niu
First submitted to arxiv on: 12 Oct 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper provides a comprehensive guide to Automated Machine Learning (AutoML), covering fundamental principles, practical implementations, and future trends. It discusses popular AutoML tools such as TPOT, AutoGluon, and Auto-Keras, while also exploring emerging topics like Neural Architecture Search (NAS) and AutoML’s applications in deep learning. The work aims to contribute to ongoing research and development in the field of AI and machine learning. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Automated Machine Learning is a way to make machines learn without needing humans to create complex algorithms. This paper helps us understand how it works, what tools are available, and where we’re headed with this technology. It’s like getting a map for a journey into the world of AI! The authors explain things in a way that makes sense even if you don’t have a technical background. |
Keywords
* Artificial intelligence * Deep learning * Machine learning
