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所在平台: Udemy |
课程主页: https://www.udemy.com/course/generative-ai/
课程评论：没有评论
**课程名称：** 生成式AI经典课程（由Martin Musiol主讲） **课程概述：** 本课程深入探讨了近年来迅速发展的生成式人工智能（GAI）。GAI作为AI领域的一个重要分支，能够生成各类数据，其能力不断提升并开始展现出令人瞩目的成果。课程旨在解答关于GAI的可能性以及如何在个人项目 H 10:38 2.11.2024及企业应用中有效利用数据生成技术等一系列关键问题。 **课程三大视角：** 1. **应用视角：** 介绍广泛的GAI应用领域，包括但不限于： * 网络安全 2.0（对抗攻击与防御） * 3D对象生成 * 文本到图像转换 * 视频到视频转换 * 超分辨率 * 交互式图像生成 * 人脸生成 * 生成艺术 * GANs数据压缩 * 领域迁移（如风格迁移、草图到图像、分割到图像） * 加密、区块链、NFTs * 创意生成器 * 视频自动化生成与预测 * 文本生成、自然语言处理模型（包括代码建议，如Co-Pilot） * GAI展望等。 课程将引导学员思考新兴项目创意，并提供将GAI模型有效实施的起点和方法。 2. **技术视角：** 重点介绍现有的GAI模型，并聚焦于核心技术而非易过时的管理代码。课程将进行一次概念性的技术 excursion，从计算图、神经网络，到深度神经网络，再到卷积神经网络（这是图像和视频生成的基础）。所涵盖的GAI架构/模型（至少在概念层面）包括： * （基础版）GAN * AutoEncoder * Variational AutoEncoder * Style-GAN * conditional GAN * 3D-GAN * GauGAN * DC-GAN * CycleGAN * GPT-3 * Progressive GAN * BiGAN * GameGAN * BigGAN * Pix2Vox * WGAN * StackGAN 等。 3. **伦理视角/伦理AI：** 讨论GAI模型相关的担忧，以及企业和政府为防止潜在危害所采取的措施。 **课程目标：** 引导学员踏上生成式AI的学习之旅，全面理解GAI的应用潜力、技术原理以及伦理考量。 **教学方式：** 通过理论讲解和案例分析，结合对关键代码部分的理解，帮助学员掌握GAI的核心概念和实践应用。
Recently, we have seen a shift in AI that wasn't very obvious. Generative Artificial Intelligence (GAI) - the part of AI that can generate all kinds of data - started to yield acceptable results, getting better and better. As GAI models get better, questions arise e.g. what will be possible with GAI models? Or, how to utilize data generation for your own projects?In this course, we answer these and more questions as best as possible.There are 3 angles that we take: Application angle: we get to know many GAI application fields, where we then ideate what further projects could emerge from that. Ultimately, we point to good starting points and how to get GAI models implemented effectively.The application list is down below.Tech angle: we see what GAI models exist. We will focus on only relevant parts of the code and not on administrative code that won't be accurate a year from now (it's one google away). Further, there will be an excursion: from computation graphs, to neural networks, to deep neural networks, to convolutional neural networks (the basis for image and video generation).The architecture list is down below.Ethical angle/ Ethical AI: we discuss the concerns of GAI models and what companies and governments do to prevent further harm.Enjoy your GAI journey!List of discussed application fields:Cybersecurity 2.0 (Adversarial Attack vs. Defense)3D Object GenerationText-to-Image TranslationVideo-to-Video TranslationSuperresolutionInteractive Image GenerationFace GenerationGenerative ArtData Compression with GANsDomain-Transfer (i.e. Style-Transfer, Sketch-to-Image, Segmentation-to-Image)Crypto, Blockchain, NFTsIdea GeneratorAutomatic Video Generation and Video PredictionText Generation, NLP Models (incl. Coding Suggestions like Co-Pilot)GAI Outlooketc.Generative AI Architectures/ Models that we cover in the course (at least conceptually):(Vanilla) GANAutoEncoderVariational AutoEncoderStyle-GANconditional GAN3D-GANGauGANDC-GANCycleGANGPT-3Progressive GANBiGANGameGANBigGANPix2VoxWGANStackGANetc.
