In recent years, the employment of deep learning methods has led to several significant breakthroughs in artificial intelligence. Different from traditional machine learning models, deep learning-based approaches are able to extract features autonomously from raw data. This allows for bypassing the feature engineering process, which is generally considered to be both error-prone and tedious. Moreover, deep learning strategies often outperform traditional models in terms of accuracy.

翻译：近年来，深度学习方法的应用推动了人工智能领域的多项重大突破。与传统机器学习模型不同，基于深度学习的方法能够自动从原始数据中提取特征，从而规避通常被认为既易出错又繁琐的特征工程过程。此外，深度学习策略在准确性方面往往优于传统模型。