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所在平台: Udemy |
课程主页: https://www.udemy.com/course/pytorch-the-complete-guide-2022/
课程评论：没有评论
**PyTorch: 2024 完整指南** 本课程是学习 PyTorch 的绝佳在线资源。尽管 TensorFlow 在深度学习领域广受欢迎，但 PyTorch 已成为全球专业人士和研究人员在人工智能和深度学习的首选库。 **课程亮点：** * **PyTorch 的优势：** 了解 PyTorch 相较于 TensorFlow 的优势，以及其背后Facebook AI Research Lab (FAIR) 的强大支持。 * **行业认可：** OpenAI、Apple 和 JPMorgan Chase 等顶尖 AI 公司都选用 PyTorch，表明其日益增长的影响力。 * **全面学习：** 课程内容涵盖 NumPy、Pandas、PyTorch张量、神经网络理论（感知器、激活函数、损失函数、反向传播、梯度）、人工神经网络、卷积神经网络 (CNN)、循环神经网络 (RNN) 等。 * **实践能力：** 学完本课程后，您将能够运用 PyTorch 独立构建各种深度学习模型，解决实际问题。 如果您想掌握一款强大的深度学习框架，并为您的 AI 项目打下坚实基础，那么“PyTorch: 2024 完整指南”将是您的不二之选。立即报名，开启您的 PyTorch 学习之旅！
Welcome to the best online course for learning about Pytorch!Although Google's Deep Learning library Tensorflow has gained massive popularity over the past few years, PyTorch has been the library of choice for professionals and researchers around the globe for deep learning and artificial intelligence.Is it possible that Tensorflow is popular only because Google is popular and used effective marketing?Why did Tensorflow change so significantly between version 1 and version 2? Was there something deeply flawed with it, and are there still potential problems?It is less well-known that PyTorch is backed by another Internet giant, Facebook (specifically, the Facebook AI Research Lab - FAIR). So if you want a popular deep learning library backed by billion dollar companies and lots of community support, you can't go wrong with PyTorch. And maybe it's a bonus that the library won't completely ruin all your old code when it advances to the next version. ;)On the flip side, it is very well-known that all the top AI shops (ex. OpenAI, Apple, and JPMorgan Chase) use PyTorch. OpenAI just recently switched to PyTorch in 2022, a strong sign that PyTorch is picking up steam.In this course you will learn everything you need to know to get started with Pytorch, including:NumPyPandasTensors with PyTorchNeural Network TheoryPerceptronsNetworksActivation FunctionsCost/Loss FunctionsBackpropagationGradientsArtificial Neural NetworksConvolutional Neural NetworksRecurrent Neural Networksand much more!By the end of this course you will be able to create a wide variety of deep learning models to solve your own problems with your own data sets.So what are you waiting for? Enroll today and experience the true capabilities of PyTorch! I'll see you inside the course!
