Train a Hotdog Image Recognition Model with Python

We all know that machines can do a lot these days, including recognizing whether or not an image has a certain object in it. But did you know that you, too, can train a model to do just that? In this guided project, you’ll learn how to train a model in Python with PyTorch, a machine learning library, to detect if a picture has a hotdog in it. This process can be repeated with any object, whether it is a bird, a plane or even Superman!

Launch an AI Hotdog Detector as a Serverless Python App

Have you ever wondered if a picture has a hotdog in it or not? Well, no longer do you have to wonder—you can now prove it! With this fun project, you’ll learn how to create and launch a web app in Python that tells you just that: whether or not a picture has a hotdog in it. Let’s settle the great debate once and for all, learning skills that can help you land your next big job or pursue your million dollar idea while you’re at it!

PyTorch: Tensor, Dataset and Data Augmentation

Data preparation plays a crucial role in effectively solving machine learning (ML) problems. PyTorch, a powerful deep learning framework, offers a plethora of tools to make data loading easy. The PyTorch: Tensor, Dataset and Data Augmentation course will provide you with a solid understanding of the basics and core principles of PyTorch, specifically focusing on tensor manipulation, dataset management, and data augmentation techniques.

Classification with PyTorch

Designed for students and enthusiasts, this course equips you with the knowledge and practical skills to build powerful and accurate classification models using PyTorch. It offers a hands-on learning experience, allowing you to apply your knowledge through coding exercises and lessons so by the end of the course, you will possess the skills to build, train, and evaluate classification models using PyTorch. "Classification with PyTorch" is a part of a PyTorch Learning Path, check Prerequisites.

Convolutional Neural Networks with PyTorch

In this course you will gain practical skills to tackle real-world image analysis and computer vision challenges using PyTorch. Uncover the power of Convolutional Neural Networks (CNNs) and explore the fundamentals of convolution, max pooling, and convolutional networks. Learn to train your models with GPUs and leverage pre-trained networks for transfer learning. . Note, this course is a part of a PyTorch Learning Path, check Prerequisites Section.