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所在平台: Udemy |
课程主页: https://www.udemy.com/course/pytorch-for-deep-learning-with-python-bootcamp/
课程评论：没有评论
课程名称：使用Python和PyTorch的深度学习训练营 课程概述：欢迎参加最优秀的在线课程，学习使用Python和PyTorch进行深度学习！PyTorch是一个开源的深度学习平台，提供了从研究原型到生产部署的无缝路径。它正迅速成为Python中最受欢迎的深度学习框架之一。PyTorch与Python的深度集成使得可以轻松使用流行的库和包来编写神经网络层。丰富的工具和库生态系统扩展了PyTorch，并支持计算机视觉、自然语言处理等多个领域的开发。 本课程重点平衡重要的理论概念与实际动手练习和项目，帮助您将课程中的概念应用到自己的数据集上！注册课程后，您将获取精心设计的笔记本，简单明了地解释概念，包括代码和解释并列展示。您还将获得幻灯片，通过易于理解的可视化方式解释理论内容。 在本课程中，我们将教您入门深度学习与PyTorch所需的全部知识，包括：NumPy、Pandas、机器学习理论、测试/训练/验证数据拆分、模型评估（回归和分类任务）、无监督学习任务、PyTorch中的张量、神经网络理论（感知器、网络、激活函数、成本/损失函数、反向传播、梯度）、人工神经网络、卷积神经网络、递归神经网络等多个主题。 课程结束时，您将能够创建多种深度学习模型，利用自己的数据集解决各种问题。那么，您还在等什么呢？今天就注册课程，体验PyTorch深度学习的真正能力吧！期待在课程中见到您！-Jose
Welcome to the best online course for learning about Deep Learning with Python and PyTorch!PyTorch is an open source deep learning platform that provides a seamless path from research prototyping to production deployment. It is rapidly becoming one of the most popular deep learning frameworks for Python. Deep integration into Python allows popular libraries and packages to be used for easily writing neural network layers in Python. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. This course focuses on balancing important theory concepts with practical hands-on exercises and projects that let you learn how to apply the concepts in the course to your own data sets! When you enroll in this course you will get access to carefully laid out notebooks that explain concepts in an easy to understand manner, including both code and explanations side by side. You will also get access to our slides that explain theory through easy to understand visualizations.In this course we will teach you everything you need to know to get started with Deep Learning with Pytorch, including:NumPyPandasMachine Learning TheoryTest/Train/Validation Data SplitsModel Evaluation - Regression and Classification TasksUnsupervised Learning TasksTensors with PyTorchNeural Network Theory PerceptronsNetworksActivation 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 Deep Learning with PyTorch! I'll see you inside the course! -Jose
