Intro to Deep Learning with PyTorch Welcome to the course!Welcome to this course on deep learning with PyTorch!Introduction to Neural NetworksLearn the concepts behind how neural networks operate and how we train them using data.Talking PyTorch with Soumith ChintalaHear from Soumith Chintala, the creator of PyTorch, about the past, present, and future of the PyTorch framework.Introduction to PyTorchLearn how to use PyTorch to build and train deep neural networks. By the end of this lesson, you will build a network that can classify images of dogs and cats with state-of-the-art performance.Convolutional Neural NetworksLearn how to use convolutional neural networks to build state-of-the-art computer vision models.Style TransferUse a deep neural network to transfer the artistic style of one image onto another image.Recurrent Neural NetworksLearn how to use recurrent neural networks to learn from sequential data such as text. Build a network that can generate realistic text one letter at a time.Sentiment Prediction RNNsHere you'll build a recurrent neural network that can accurately predict the sentiment of movie reviews.Deploying PyTorch ModelsIn this lesson, we'll walk through a tutorial showing how to deploy PyTorch models with Torch Script.CompanyAbout Us Why Udacity? Blog In the News Jobs at Udacity Become a Mentor Partner with Udacity ResourcesCatalog Career Outcomes Help and FAQ Scholarships Resource Center Udacity SchoolsSchool of Artificial Intelligence School of Autonomous Systems School of Business School of Cloud Computing School of Cybersecurity School of Data Science School of Executive Leadership School of Product Management School of Programming and Development Career Resources Featured ProgramsBusiness Analytics SQL AWS Cloud Architect Data Analyst Intro to Programming Digital Marketing Self Driving Car Engineer Only at UdacityArtificial Intelligence Deep Learning Digital Marketing Flying Car and Autonomous Flight Engineer Intro to Self-Driving Cars Machine Learning Engineer Robotics Software Engineer