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With the emerging trend of GPT models, we have established a framework calledAutoML-GPT that integrates a comprehensive set of tools and libraries. Thisframework grants users access to a wide range of data preprocessing techniques,feature engineering methods, and model selection algorithms. Through aconversational interface, users can specify their requirements, constraints,and evaluation metrics. Throughout the process, AutoML-GPT employs advancedtechniques for hyperparameter optimization and model selection, ensuring thatthe resulting model achieves optimal performance. The system effectivelymanages the complexity of the machine learning pipeline, guiding users towardsthe best choices without requiring deep domain knowledge. Through ourexperimental results on diverse datasets, we have demonstrated that AutoML-GPTsignificantly reduces the time and effort required for machine learning tasks.Its ability to leverage the vast knowledge encoded in large language modelsenables it to provide valuable insights, identify potential pitfalls, andsuggest effective solutions to common challenges faced during model training.

AutoML-GPT: Large Language Model for AutoML