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所在平台: Udemy |
课程主页: https://www.udemy.com/course/practical-transfer-learning-in-python/
课程评论：没有评论
课程总结：实用迁移学习（深度学习）在Python中的应用 本课程以“不要做英雄”为主题，倡导学员借助已有的深度学习研究成果来解决实际问题，而不必追求研究的顶尖水平。我们将聚焦于迁移学习，这是一种能让我们利用已有模型知识来应对新挑战的技术。课程中将展示如何在图像分类任务中应用迁移学习，具体示例包括如何利用识别自行车的知识来识别汽车。 课程将深入讨论几种实现迁移学习的方法，包括预训练模型、微调和特征提取技术。通过参与课程，学员将获得实际的代码示例和技术应用的深刻理解，旨在提升行业中的具体应用准确性。总之，这是一门实用性极强的课程，鼓励学员们积极加入，共同学习和应用迁移学习的强大能力。
Don't be Hero. as It is well said..Let;s Enroll and utilize works of Hero for our problems.Everyone can not do research like Yann Lecun or Andrew Ng. They are focused on improving machine learning algorithms for better world.But as an individual and for industry, we are more concern with specific application and its accuracy.Transfer Learning is the solution for many existing problems. Transfer learning uses existing knowledge of previously learned model to new frontier.I will demonstrate code to do Transfer Learning in Image Classification.Knowledge gain to recognize cycle and bike can be used to recognize car.There are various ways we can achieve transfer learning. I will discuss Pre trained model, Fine tunning and feature extraction techniques.Once again. Let's not be Hero. and enroll in this course.
