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所在平台: Udemy |
课程主页: https://www.udemy.com/course/pytorch-ultimate/
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课程名称：PyTorch 完全指南：从基础到前沿 课程概述：PyTorch 是由 Facebook 开发的一个 Python 框架，用于开发和部署深度学习模型。它是当前最受欢迎的深度学习框架之一。在本课程中，您将学习开发和应用深度学习模型所需的一切知识，涵盖回归、分类、卷积神经网络（CNN）、递归神经网络（RNN）、生成对抗网络（GAN）、自然语言处理（NLP）、推荐系统等多个相关领域。此外，还将介绍诸如 Transformer、YOLOv7、ChatGPT 等前沿模型和架构。课程强调理解基本概念及其实施方法，您将面临独立解决问题的挑战，然后我将展示我的解决方案。 课程内容包括： - 深度学习简介 - 高级理解 - 感知机 - 层、激活函数、损失函数、优化器 - 张量处理及其创建和特性 - 自动梯度计算（autograd） - 建模简介，包括从零开始的线性回归 - PyTorch 模型训练理解 - 批处理、数据集和数据加载器 - 超参数调整、模型保存和加载 - 分类模型（多标签分类、多类分类） - 卷积神经网络理论及图像分类模型开发 - 图像变换、音频分类和目标检测理论 - 开发 YOLO v7 和 YOLO v8 目标检测模型 - 风格迁移理论及模型开发 - 预训练模型与迁移学习 - 递归神经网络及 LSTM 模型开发 - 推荐系统与矩阵分解、自编码器 - Transformer 理论，包括视觉 Transformer（ViT），并应用于自定义数据集 - 生成对抗网络、半监督学习 - 自然语言处理（NLP），词嵌入基础与神经网络 - 使用 One-Hot 编码和 GloVe 开发情感分析模型 - 预训练 NLP 模型的应用 - 模型调试、Hooks 和部署策略（包括本地和云端部署，特别是 Google Cloud） - 其他主题，如 ChatGPT、ResNet 和极限学习机（ELM） 立即注册课程，学习一流的技术，提升您的职业生涯！ 最好的祝福， Bert
PyTorch is a Python framework developed by Facebook to develop and deploy Deep Learning models. It is one of the most popular Deep Learning frameworks nowadays. In this course you will learn everything that is needed for developing and applying Deep Learning models to your own data. All relevant fields like Regression, Classification, CNNs, RNNs, GANs, NLP, Recommender Systems, and many more are covered. Furthermore, state of the art models and architectures like Transformers, YOLOv7, or ChatGPT are presented. It is important to me that you learn the underlying concepts as well as how to implement the techniques. You will be challenged to tackle problems on your own, before I present you my solution.In my course I will teach you:Introduction to Deep Learninghigh level understandingperceptronslayersactivation functionsloss functionsoptimizersTensor handlingcreation and specific features of tensorsautomatic gradient calculation (autograd)Modeling introduction, incl. Linear Regression from scratchunderstanding PyTorch model trainingBatchesDatasets and DataloadersHyperparameter Tuningsaving and loading modelsClassification modelsmultilabel classificationmulticlass classificationConvolutional Neural NetworksCNN theorydevelop an image classification modellayer dimension calculationimage transformationsAudio Classification with torchaudio and spectrogramsObject Detectionobject detection theorydevelop an object detection modelYOLO v7, YOLO v8Faster RCNNStyle TransferStyle transfer theorydeveloping your own style transfer modelPretrained Models and Transfer LearningRecurrent Neural NetworksRecurrent Neural Network theorydeveloping LSTM modelsRecommender Systems with Matrix FactorizationAutoencodersTransformersUnderstand Transformers, including Vision Transformers (ViT)adapt ViT to a custom datasetGenerative Adversarial NetworksSemi-Supervised LearningNatural Language Processing (NLP)Word Embeddings IntroductionWord Embeddings with Neural NetworksDeveloping a Sentiment Analysis Model based on One-Hot Encoding, and GloVeApplication of Pre-Trained NLP modelsModel DebuggingHooksModel Deploymentdeployment strategiesdeployment to on-premise and cloud, specifically Google CloudMiscellanious TopicsChatGPTResNetExtreme Learning Machine (ELM)Enroll right now to learn some of the coolest techniques and boost your career with your new skills.Best regards,Bert
