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所在平台: Udemy |
课程主页: https://www.udemy.com/course/fundamentals-deep-learning-concept-pytorch/
课程评论：没有评论
课程名称：初学者深度学习：核心概念与PyTorch 课程概述：你是否对人工智能（AI）、机器学习和人工神经网络感兴趣？是否因为深度学习听起来过于技术化而感到畏惧？你是否曾观看深度学习的视频，却始终感觉自己“没有明白”？我也曾经历过这种情况！我没有工程背景，是自学编程的，但AI仍然觉得遥不可及。这个课程旨在帮助您节省数月的挫折，轻松理解深度学习。完成课程后，您将能够应对更高级、前沿的AI主题。 在本课程中：我们假设您只有最少的先前知识（只需基本的Python知识），不需要工程或计算机科学的背景。对于深度学习所需的所有数学知识，我们会逐步一同学习。我们将“重新发明”一个深度神经网络，让您深入了解其基本机制。这将帮助您自信地理解深度学习并对该主题产生直观的感觉。同时，我们还将使用PyTorch和PyTorch Lightning从零开始构建一个基本的神经网络，训练一个用于手写数字识别的MNIST模型。 完成本课程后，您将获得对深度学习的“直观”理解，能够自信地进一步拓展您的知识。如果您再次回到之前难以理解的流行课程（如Andrew Ng的课程或Jeremy Howard的Fastai课程），您会惊喜地发现自己能理解更深入的内容。您将能够理解Geoffrey Hinton或Andrej Karpathy在相关文章或特斯拉自动驾驶日上所说的内容。 您将具备理論和实践知识，能够开始探索更高级的神经网络架构，如卷积神经网络（CNN）、递归神经网络（RNN）、变换器等，开始迈向人工智能的前沿领域及有监督和无监督学习等话题。您还可以使用PyTorch和有监督学习开始尝试自己的AI项目。 本课程非常适合以下人群： - 对深度学习和PyTorch感兴趣，但在核心概念上有困难的学习者 - 来自非工程背景、希望转行的人员 - 熟悉基础知识但希望深入探索更高级知识的人 - 已在使用深度学习模型，但想进一步提升理解的人 - 希望提升职业生涯的Python开发者 这门9.5小时的课程将教授您所有基本概念以及知识的应用。您将获得40个可下载资源、终身访问权限、30天退款保证和结业证书。让我们一起探索深度学习的奇妙世界吧！
Are you interested in Artificial Intelligence (AI), Machine Learning and Artificial Neural Network?Are you afraid of getting started with Deep Learning because it sounds too technical?Have you been watching Deep Learning videos, but still don't feel like you "get" it?I've been there myself! I don't have an engineering background. I learned to code on my own. But AI still seemed completely out of reach.This course was built to save you many months of frustration trying to decipher Deep Learning. After taking this course, you'll feel ready to tackle more advanced, cutting-edge topics in AI.In this course:We assume as little prior knowledge as possible. No engineering or computer science background required (except for basic Python knowledge). You don't know all the math needed for Deep Learning? That's OK. We'll go through them all together - step by step.We'll "reinvent" a deep neural network so you'll have an intimate knowledge of the underlying mechanics. This will make you feel more comfortable with Deep Learning and give you an intuitive feel for the subject.We'll also build a basic neural network from scratch in PyTorch and PyTorch Lightning and train an MNIST model for handwritten digit recognition.After taking this course:You'll finally feel you have an "intuitive" understanding of Deep Learning and feel confident expanding your knowledge further.If you go back to the popular courses you had trouble understanding before (like Andrew Ng's courses or Jeremy Howards' Fastai course), you'll be pleasantly surprised at how much more you can understand.You'll be able to understand what experts like Geoffrey Hinton are saying in articles or Andrej Karpathy is saying during Tesla Autonomy Day.You'll be well equipped with both practical and theoretical understanding to start exploring more advanced neural network architectures like Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), transformers, etc. and start your journey towards the cutting edge of AI, Supervised and Unsupervised learning, and more.You can start experimenting with your own AI projects using PyTorch and Supervised LearningThis course is perfect for you if you are:Interested in Deep Learning and PyTorch but struggling with the core conceptsSomeone from a non-engineering background transitioning into an engineering careerFamiliar with the basics but wish explore more advanced knowledge.Already working with Deep Learning models, but want to supercharge your understandingA Python Developer, looking to advance your careerThis 9.5 hour course will teach you all the basic concepts as well as the application of your knowledge. You get 40 downloadable resources, full lifetime access, 30-Day Money-Back Guarantee and a Certificate of Completion. So what stops you from taking a deep dive into the amazing world of Deep Learning?
