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所在平台: Udemy |
课程主页: https://www.udemy.com/course/datasciencecovid-19-pneumonia-classificationdeep-learning/
课程评论：没有评论
**课程总结：数据科学：COVID-19肺炎分类（深度学习）** 本课程是一项实际操作的深度学习项目，旨在教授学员如何利用卷积神经网络 (CNN) 分析肺部X光片，以检测COVID-19病毒感染。课程强调通过深度学习技术对X光图像进行像素级分析，无需PCR或RDT检测，即可实现对COVID-19引起的肺炎的准确分类，准确率可达98%左右。 **核心内容：** * **COVID-19检测原理：** 了解COVID-19如何影响肺部并引起肺炎，以及深度学习和CNN在此过程中的应用。 * **CNN模型构建与训练：** 学习如何从零开始构建、编译和训练一个CNN模型，用于COVID-19肺炎的分类。 * **数据处理与增强：** 掌握数据集的导入、探索、可视化、数据增强和归一化等关键步骤。 * **模型评估与预测：** 学习如何评估模型的性能，对新数据进行预测，并将训练好的模型保存以备将来使用。 **课程结构（任务分解）：** 1. **Google Colab环境与库导入：** 熟悉Colab环境并导入所需的Python库。 2. **数据集的获取与探索：** 导入、克隆并初步了解COVID-19相关的X光数据集。 3. **数据可视化：** 对X光图像进行可视化展示，以便更好地理解数据特征。 4. **数据增强与归一化：** 提高模型的泛化能力，使模型更能适应各种输入。 5. **CNN模型构建：** 设计和搭建卷积神经网络的结构。 6. **模型编译与训练：** 配置模型参数并开始训练过程。 7. **模型评估与测试：** 评估模型在测试集上的表现，并进行预测。 **课程亮点：** * **实践导向：** 课程专注于实际操作，避免不必要的理论讲解，内容“简短、精炼、直击要点”。 * **高就业潜力：** 掌握的技能可应用于其他基于图像的诊断，如皮肤癌检测、普通肺炎检测、脑部缺陷分析和视网膜图像分析等，有助于提升职业竞争力。 * **证书认可：** 完成课程将获得完成证书，可添加到简历中，在当前疫情形势下对职业发展极具助力。 * **即学即用：** 鼓励学员立即动手实践，通过训练和测试COVID-19 CNN模型来学习。 本课程适合希望学习如何利用深度学习进行医学图像分析，特别是COVID-19肺炎检测的学员。
Would you like to learn how to Predict if someone has a Coronavirus infection through the X-ray of their lungs?Would you like to build a Convolutional Neural Network model using Deep learning to detect Covid-19?If the answer to any of the above questions is "YES", then this course is for you.Enroll Now in this course and learn how to detect Coronavirus in a patient through the X-Ray reports of their lungs. This is the You might be wondering if it is really possible to detect Coronavirus in a patient through the X-Ray reports of their lungs. YES, IT IS POSSIBLE THROUGH DEEP LEARNING AND CONVOLUTIONAL NEURAL NETWORKS.As we know, Coronavirus affects the lungs of the victims and causes Pneumonia especially termed as COVID Pneumonia. Through Deep learning technologies and Convolutional Neural Networks, we can analyze the X-Ray reports of lungs to the Pixel level. Without any PCR or RDT test, Coronavirus can be detected if the virus has infected the lungs of the patients through Convolutional Neural Network with approximate 98 percent accuracy.This is a hands-on Data Science guided project on Covid-19 Pneumonia Classification. No unnecessary lectures. As our students like to say:"Short, sweet, to the point course"The same techniques can be used in:Skin cancer detectionNormal pneumonia detectionBrain defect analysis Retinal Image AnalysisAnd any other diseases that use image-based reporting, like X-ray reports.Enroll now and You will receive a CERTIFICATE OF COMPLETION and we encourage you to add this project to your resume. At a time when the entire world is troubled by Coronavirus, this project can catapult your career to another level.So bring your laptop and start building, training and testing the Data Science Covid 19 Convolutional Neural Network model right now.You will learn:How to detect Coronavirus infection using the Xray Report of the lungs of PatientsClassify COVID 19 based on x-ray images using deep learningLearn to Build and train a Convolutional neural networkMake a prediction on new data using CNN ModelWe will be completing the following tasks:Task 1: Getting Introduced to Google Colab Environment & importing necessary librariesTask 2: Importing, Cloning & Exploring DatasetTask:3 Data visualization (Image Visualization)Task 4: Data augmentation & NormalizationTask 5: Building Convolutional neural network modelTask 6: Compiling & Training CNN ModelTask 7: Performance evaluation & Testing the model & saving the model for future useSo, grab a coffee, turn on your laptop, click on the ENROLL NOW button, and start learning right now.
