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所在平台: Udemy |
课程主页: https://www.udemy.com/course/deep-learning-gans-and-variational-autoencoders/
课程评论：没有评论
课程名称：深度学习：生成对抗网络与变分自编码器 课程概述：您是否曾想过类似OpenAI DALL-E、Midjourney和Stable Diffusion等人工智能技术是如何运作的？在本课程中，您将学习这些开创性应用的基础知识。变分自编码器和生成对抗网络（GAN）是最近深度学习和机器学习领域最有趣的发展之一。深度学习先驱Yann LeCun曾表示，近年来最重要的发展是对抗训练，即GAN。 生成对抗网络是由两个神经网络相互竞争而组成的。什么是无监督学习？无监督学习意味着我们并不是试图将输入数据映射到目标，而是仅仅想要了解输入数据的结构。一旦我们掌握了这种结构，便可以做到一些很酷的事情。例如，生成诗歌——我们过去曾做过这样的例子。但诗歌是非常具体的内容，那写作一般的文本呢？如果我们能理解语言的结构，就可以生成任何类型的文本。实际上，大公司正在投资研究机器如何撰写新闻。 如果我们回到诗歌中，去掉文字呢？那么我们得到了艺术。通过学习艺术的结构，我们可以创造更多的艺术。那么音乐的艺术呢？如果我们学习音乐的结构，就能创作新的音乐。想象一下，您在收听的排行榜前40首歌曲是机器人而非人类创作的。可能性是无穷的！ 您可能会问：“这门课程与第一门无监督深度学习课程有什么不同？”在第一门课程中，我们仍然试图学习数据的结构，但原因不同。我们的目的是为了改进监督训练，这已经得到证明。在这门新课程中，我们的目的是学习数据结构，以便生成更像原始数据的内容。这本身就很酷，但我们还将结合来自贝叶斯机器学习、强化学习和博弈论的概念，这让它更具吸引力！ 感谢您的阅读，我们在课堂上见！如果您无法实现它，那您就不理解它。正如伟大的物理学家理查德·费曼所说：“我无法创造的东西，我就不理解。”我的课程是唯一一门教您怎样从零开始实现机器学习算法的课程。其他课程只教您如何将数据插入库中，但您真的需要帮助来编写三行代码吗？在使用10个数据集做同样的事情后，您会意识到您并没有学习到10件事情，而是只学到了一件事情，并重复了相同的三行代码10次。 建议先修课程：微积分、概率论、面向对象编程、Python编程（if/else、循环、列表、字典、集合）、Numpy编程（矩阵和向量运算）、线性回归、梯度下降、了解如何在Theano或TensorFlow中构建前馈和卷积神经网络。 课程的独特特点：详细解释每一行代码——如有意见，请随时联系我。没有浪费时间在键盘上“打字”，像其他课程那样——说实话，没有人能在20分钟内从零开始写出值得学习的代码。不怕大学水平的数学，获取其他课程遗漏的重要算法细节。
Ever wondered how AI technologies like OpenAI DALL-E, Midjourney, and Stable Diffusion really work? In this course, you will learn the foundations of these groundbreaking applications.Variational autoencoders and GANs have been 2 of the most interesting developments in deep learning and machine learning recently.Yann LeCun, a deep learning pioneer, has said that the most important development in recent years has been adversarial training, referring to GANs.GAN stands for generative adversarial network, where 2 neural networks compete with each other.What is unsupervised learning?Unsupervised learning means we're not trying to map input data to targets, we're just trying to learn the structure of that input data.Once we've learned that structure, we can do some pretty cool things.One example is generating poetry - we've done examples of this in the past.But poetry is a very specific thing, how about writing in general?If we can learn the structure of language, we can generate any kind of text. In fact, big companies are putting in lots of money to research how the news can be written by machines.But what if we go back to poetry and take away the words?Well then we get art, in general.By learning the structure of art, we can create more art.How about art as sound?If we learn the structure of music, we can create new music.Imagine the top 40 hits you hear on the radio are songs written by robots rather than humans.The possibilities are endless!You might be wondering, "how is this course different from the first unsupervised deep learning course?"In this first course, we still tried to learn the structure of data, but the reasons were different.We wanted to learn the structure of data in order to improve supervised training, which we demonstrated was possible.In this new course, we want to learn the structure of data in order to produce more stuff that resembles the original data.This by itself is really cool, but we'll also be incorporating ideas from Bayesian Machine Learning, Reinforcement Learning, and Game Theory. That makes it even cooler!Thanks for reading and I'll see you in class. =)"If you can't implement it, you don't understand it"Or as the great physicist Richard Feynman said: "What I cannot create, I do not understand".My courses are the ONLY courses where you will learn how to implement machine learning algorithms from scratchOther courses will teach you how to plug in your data into a library, but do you really need help with 3 lines of code?After doing the same thing with 10 datasets, you realize you didn't learn 10 things. You learned 1 thing, and just repeated the same 3 lines of code 10 times...Suggested Prerequisites:CalculusProbabilityObject-oriented programmingPython coding: if/else, loops, lists, dicts, setsNumpy coding: matrix and vector operationsLinear regressionGradient descentKnow how to build a feedforward and convolutional neural network in Theano or TensorFlowWHAT ORDER SHOULD I TAKE YOUR COURSES IN?:Check out the lecture "Machine Learning and AI Prerequisite Roadmap" (available in the FAQ of any of my courses, including the free Numpy course)UNIQUE FEATURESEvery line of code explained in detail - email me any time if you disagreeNo wasted time "typing" on the keyboard like other courses - let's be honest, nobody can really write code worth learning about in just 20 minutes from scratchNot afraid of university-level math - get important details about algorithms that other courses leave out
