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所在平台: Udemy |
课程主页: https://www.udemy.com/course/tensorflow-hub-deep-learning-computer-vision-nlp/
课程评论：没有评论
课程名称：TensorFlow Hub：深度学习、计算机视觉与自然语言处理 课程概述：深度学习是利用人工神经网络解决复杂问题和商业问题的一种应用技术。这种技术目前已在许多领域得到了实际应用，如自动驾驶汽车、新药开发、疾病诊断、自动生成新闻、面部识别、产品推荐和股票价格预测等。人工神经网络旨在模拟人类大脑的工作方式，是机器学习领域中最先进的技术之一。谷歌的TensorFlow是实现这些应用的最常用库之一，它支持高级的人工神经网络架构。此外，还有一个名为TensorFlow Hub的库，包含了用于解决各种问题的预训练神经网络，主要集中在计算机视觉和自然语言处理领域。使用TensorFlow Hub的一个优势是，无需从头开始训练神经网络，谷歌提供了数百个现成的模型，只需加载并在自己的项目中使用。此外，获得结果所需的代码行数也非常少！ 在本课程中，您将获得一些主要TensorFlow Hub模型的实用概述，这些模型可应用于深度学习项目的开发。课程结束时，您将掌握使用TensorFlow Hub构建适用于商业问题的复杂解决方案所需的所有工具。您将实施的项目包括： - 五种花卉的分类 - 超过80种不同物体的检测 - 使用风格迁移创建新图像 - 利用生成对抗网络（GAN）填补图像的缺失部分 - 视频中的动作识别 - 文本极性分类（正面和负面） - 使用问答（Q&A）数据集查找相似文档 - 音频分类 所有实现过程将在Google Colab在线进行，无需担心在自己机器上安装和配置工具！课程含有超过50节课和7个小时以上的视频内容。
Deep Learning is the application of artificial neural networks to solve complex problems and commercial problems. There are several practical applications that have already been built using these techniques, such as: self-driving cars, development of new medicines, diagnosis of diseases, automatic generation of news, facial recognition, product recommendation, forecast of stock prices, and many others! The technique used to solve these problems is artificial neural networks, which aims to simulate how the human brain works. They are considered to be the most advanced techniques in the Machine Learning area.One of the most used libraries to implement this type of application is Google TensorFlow, which supports advanced architectures of artificial neural networks. There is also a repository called TensorFlow Hub which contains pre-trained neural networks for solving many kinds of problems, mainly in the area of Computer Vision and Natural Language Processing. The advantage is that you do not need to train a neural network from scratch! Google itself provides hundreds of ready-to-use models, so you just need to load and use them in your own projects. Another advantage is that few lines of code are needed to get the results!In this course you will have a practical overview of some of the main TensorFlow Hub models that can be applied to the development of Deep Learning projects! At the end, you will have all the necessary tools to use TensorFlow Hub to build complex solutions that can be applied to business problems. See below the projects that you are going to implement:Classification of five species of flowersDetection of over 80 different objectsCreating new images using style transferUse of GAN (generative adversarial network) to complete missing parts of imagesRecognition of actions in videosText polarity classification (positive and negative)Use of a question and answer (Q & A) dataset to find similar documentAudio classificationAll implementations will be done step by step using Google Colab online, so you do not need to worry about installing and configuring the tools on your own machine! There are more than 50 classes and more than 7 hours of videos!
