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所在平台: Udemy |
课程主页: https://www.udemy.com/course/artem-ex-machina/
课程评论：没有评论
课程名称：Artem Ex Machina：从零开始成为人工智能艺术家 课程概述： 您知道计算机可以生成图像艺术吗？您是否想过它们是如何做到的？人工智能（AI）生成的艺术作品在拍卖中可以卖出数千美元。欢迎来到Artem Ex Machina™！在这里，您将学习如何成为人工智能（AI）艺术大师，通过构建、训练和应用生成对抗网络（GANs）来创造AI艺术。该课程独特之处在于结合了三个要素：从头开始构建、训练和使用GAN；应用预先训练的GAN以制作美丽的AI艺术；开始、维护和管理AI艺术项目。 通过完成本课程，您将能够： - 使用自己的一组训练图像构建和训练GAN； - 使用免费且高质量的预训练GAN模型创建AI艺术作品； - 理解神经网络（特别是GAN）的工作原理； - 有效管理AI艺术项目。 本课程使用Python作为编程语言，您将能够构建、训练和使用自己的GAN。除了获得开发和诊断这些深度学习模型的实用能力外，您还将深入理解其理论。由于有效管理和分享GAN背后的工作环境是生成艺术家工作流程的重要组成部分，课程还将提供与AI艺术兼容的Docker容器，并教您如何有效使用它们。理解GAN的工作原理以及构建它们的能力，将为您在数据科学领域提供强大的竞争优势。此外，您还将学习如何利用经过数千小时训练的预训练模型，创造高质量艺术作品。您将能够在自己的本地计算机上和使用图形处理单元（GPU）的远程高性能计算服务（如Google Colab）上工作。 课程分为六个部分，最后以三个顶级项目结束，您可以将其添加到您的作品集： 1. 引言：学习如何设置本地工作环境，以及如何训练和诊断手写数字GAN。 2. 生成对抗网络（GAN）是什么？学习GAN的工作原理及其训练方法。 3. AI艺术项目：了解本地与远程工作的原则以及AI艺术项目管理的方法，并高效下载GAN训练所需的bulk图像。 4. GAN架构：从头开始构建和训练GAN模型，生成复杂的灰度和彩色图像。 5. GAN+CLIP：学习如何使用预训练模型生成美丽的AI艺术。 6. 顶级项目：完成三个顶级项目，以巩固您在课程中学到的知识。 现在就开始您的Artem Ex Machina™之旅吧！
Did you know that computers can generate pictorial art? Have you ever wondered how can they do that? Did you know that the art generated by Artificial Intelligence (AI) has been sold on auctions for thousands of $$$?Welcome to Artem Ex Machina™! Here you will learn how to become Artificial Intelligence (AI) Artisan by building, training and applying Generative Artificial Networks (GANs) - deep learning networks behind AI generated art. What makes this course unique is the combination of three elements:Building, training and using GANs from scratchApplying pre-trained GANs for beautiful AI ArtsStarting, maintaining and managing AI Arts projectsBy the end of this course you will, therefore, be able to:Build and train GANs using your own set of training imagesCreate pieces of AI Arts with publicly available, FREE, and amazing quality pre-trained GANs modelsUnderstand how Neural Networks, in general, and GANs, in particular, workEffectively manage AI Arts projects To get a taster on the kind of images you'll be able to generate by completing this course, have a look at the logo of this course, which has 6 examples of images generated with GANs:) The course uses Python as a programming language upon which you'll be able to build, train and use your own GANs. Not only you'll gain practical capabilities when it comes to developing and diagnosing these deep learning models but also you'll gain a proper understanding of theory behind them. Since managing and, potentially, sharing your working environment behind GANs is an important part of the workflow of the generative artist, an integral part of the course is provision of AI-Art-compatible Docker containers and teaching you how to effectively use them. Understanding how GANs work combined with the ability to build them, will give you a strong generative artisanship acumen, and hence strong competitive advantage in the world of Data Science. In addition to that you'll learn how to make an effective use of pre-trained models that were trained for thousands of hours, to create high quality art. Therefore, you'll be able to work on your own local computer as well as remote high performance computing service such as Google Colab using Graphic Processing Units! The course is split into 6 sections culminating with a 3 capstone projects that you can add to your portfolio:Introduction. Here you'll learn how to setup your local working environment PLUS how to train and diagnose a hand-written digits GANWhat is a Generative Adversarial Network? Here you'll learn how GANs work and how they are trained PLUS how to train and apply GAN of images of clothing AI Arts projects. Here you'll learn how to work locally vs how to work remotely and principles of AI Arts project management PLUS how to efficiently download bulk of images for your GAN trainingGAN architectures. Here you'll learn how to build and train GAN models from scratch to produce complex grayscale and colour images GAN+CLIP. Here you'll learn how to use pre-trained models for beautiful AI Arts generationCapstone projects. Here you'll have the chance to complete three capstone projects to consolidate what you've learnt in the course. Start you Artem Ex Machina™ journey now!
