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所在平台: Udemy |
课程主页: https://www.udemy.com/course/hands-on-tensorboard-for-pytorch-developers/
课程评论：没有评论
**Coursera 课程总结：PyTorch 开发者的 TensorBoard 实战** 本课程由拥有 23 年工程研发经验、并领导过人工智能团队的 Joe Papa 讲授，旨在帮助 PyTorch 开发者掌握 TensorBoard 的可视化能力，从而有效地进行机器学习模型的可视化。 TensorBoard 是 TensorFlow 的一个可视化库，可以绘制训练过程、张量和图。自 PyTorch 1.1 版本起，TensorBoard 已获得原生支持。 **课程亮点：** * **快速入门：** 介绍 TensorBoard 的基本概念及其在 PyTorch 中的应用。 * **实战演练：** 课程内容充斥着实际操作示例，让学习者能够亲手实践。 * **事件写入与可视化：** 学习如何编写 TensorBoard 事件，并通过运行 TensorBoard 来直观展示 PyTorch 神经网络的训练进度。 * **多维度可视化：** 掌握可视化标量值、图像、文本等多种数据类型，并将其保存为事件。 * **全面的日志记录：** 学习在 PyTorch 中记录常见的 TensorBoard 事件，包括标量、图像、音频、直方图、文本、嵌入（embedding）以及反向传播（back-propagation）。 **学习目标：** 完成本课程后，学员将能够自信地将 TensorBoard 可视化应用于实际的 PyTorch 项目中。 **讲师简介：** Joe Papa 拥有电机工程学硕士学位，在工程研发领域拥有超过 23 年的经验。他曾领导人工智能团队，在 Booz Allen 和 Perspecta Labs 开发深度学习模型。此外，他还是 Mentorship.ai 的创始人，并为数百名数据科学家提供机器学习、深度学习和人工智能方面的指导。他在 Udemy 上也教授过超过 6,000 名学生编程课程，例如 MATLAB。
TensorBoard is a visualization library for TensorFlow that plots training runs, tensors, and graphs. TensorBoard has been natively supported since the PyTorch 1.1 release. In this course, you will learn how to perform Machine Learning visualization in PyTorch via TensorBoard. This course is full of practical, hands-on examples. You will begin with a quick introduction to TensorBoard and how it is used to plot your PyTorch training models. You will learn how to write TensorBoard events and run TensorBoard with PyTorch to obtain visualizations of the training progress of a neural network. You will visualize scalar values, images, text and more, and save them as events. You will log events in PyTorch-for example, scalar, image, audio, histogram, text, embedding, and back-propagation.By the end of the course, you will be confident enough to use TensorBoard visualizations in PyTorch for your real-world projects.About the AuthorJoe Papa has an MSEE and over 23 years' experience in engineering R & D. He has led AI teams and developed Deep Learning models at Booz Allen and Perspecta Labs. Joe is also the founder of Mentorship.ai and has mentored hundreds of data scientists in Machine Learning, Deep Learning, and AI. He has taught over 6,000 students on Udemy in programming courses such as MATLAB.
