深度学习与机器学习在大数据分析与管理中的应用：TensorFlow 预训练模型
机器学习
2025-11-20 v3 人工智能
摘要
探讨了 TensorFlow 预训练模型在深度学习中的应用，着重提供图像分类和目标检测等任务的实用指导。该研究涵盖包括 ResNet、MobileNet 和 EfficientNet 在内的现代网络架构，并通过实际案例和实验演示了迁移学习的有效性。 presented a comparison of linear probing and model fine-tuning, supplemented by visualizations using techniques like PCA, t-SNE, and UMAP, allowing for an intuitive understanding of the impact of these approaches. The work provides complete example code and step-by-step instructions, offering valuable insights for both beginners and advanced users. By integrating theoretical concepts with hands-on practice, the paper equips readers with the tools necessary to address deep learning challenges efficiently.
引用
@article{arxiv.2409.13566,
title = {Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Tensorflow Pretrained Models},
author = {Keyu Chen and Ziqian Bi and Qian Niu and Junyu Liu and Benji Peng and Sen Zhang and Ming Liu and Xinyuan Song and Zekun Jiang and Tianyang Wang and Ming Li and Xuanhe Pan and Jiawei Xu and Jinlang Wang and Pohsun Feng},
journal= {arXiv preprint arXiv:2409.13566},
year = {2025}
}
备注
This book contains 148 pages and 7 figures