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所在平台: Udemy |
课程主页: https://www.udemy.com/course/train-and-deploy-yolox-object-detection-models-to-the-cloud/
课程评论：没有评论
课程名称：深度学习物体检测：训练与部署 YOLOX 概述：物体检测算法无处不在。随着2010年代初期更高效模型的出现，这些基于深度学习的算法正在实现前所未有的性能提升。本课程将带你踏上一段精彩的旅程，逐步掌握不同的概念。我们将从理解物体检测算法的工作原理开始，到将其部署到云端，并在此过程中观察最佳实践。 你将学习到： - 深度学习之前的物体检测算法，如Haarcascades - 深度学习算法，如卷积神经网络、YOLO和YOLOX - 物体检测标注格式，如Pascal VOC - 使用Remo创建自定义数据集 - 将自定义数据集转换为Pascal VOC格式 - 使用自定义数据集对YOLOX模型进行微调和测试 - 将微调后的模型转换为Onnx格式 - 使用Wandb进行实验跟踪 - API的工作原理以及使用Fastapi构建自己的API - 将API部署到云端 - 使用Locust对已部署的API进行负载测试 - 在C++中运行物体检测模型 如果你想在职业生涯中更进一步，这门课程非常适合你，我们也非常期待帮助你实现目标！本课程由Neuralearn提供，与Neuralearn的其他课程一样，我们非常重视反馈。你的评论和论坛中的问题将帮助我们改进课程。请随时在论坛上提出尽可能多的问题，我们会尽快回复。祝你学习愉快！
Object detection algorithms are everywhere. With creation of much more efficient models from the early 2010s, these algorithms which now are built using deep learning models are achieving unprecedented performances.In this course, we shall take you through an amazing journey in which you'll master different concepts with a step by step approach. We shall start from understanding how object detection algorithms work, to deploying them to the cloud, while observing best practices.You will learn:Pre-deep learning object detection algorithms like HaarcascadesDeep Learning algorithms like Convolutional neural networks, YOLO and YOLOXObject detection labeling formats like Pascal VOC.Creation of a custom dataset with RemoConversion of our custom dataset to the Pascal VOC format.Finetuning and testing YOLOX model with custom datasetConversion of finetuned model to Onnx formatExperiment tracking with WandbHow APIs work and building your own API with FastapiDeploying an API to the CloudLoad testing a deployed API with LocustRunning object detection model in c++If you are willing to move a step further in your career, this course is destined for you and we are super excited to help achieve your goals!This course is offered to you by Neuralearn. And just like every other course by Neuralearn, we lay much emphasis on feedback. Your reviews and questions in the forum, will help us better this course. Feel free to ask as many questions as possible on the forum. We do our very best to reply in the shortest possible time.Enjoy!!!
