Course
Learn Image Classification with PyTorch
Learn how to use Python to build image classification models using CNNs and vision transformers in this PyTorch tutorial.
This course includes
This course includes
Skill level
IntermediateTime to complete
Average based on combined completion rates — individual pacing in lessons, projects, and quizzes may vary5 hoursProjects
2Prerequisites
2 coursesWe suggest you complete the following courses before you get started with Learn Image Classification with PyTorch:- Intro to PyTorch and Neural Networks
- PyTorch for Classification
About this course
Get ready to start your journey into the exciting world of image classification! In this course, you will learn how to build and train deep-learning models for image recognition using Python. You will explore convolutional neural networks (CNNs), vision transformers (ViTs), and detection transformers (DETR) to classify images, detect objects, and understand visual data. You will also learn how to preprocess images, apply data augmentation, and fine-tune pretrained models to improve accuracy.
Skills you'll gain
Process and transform images for deep learning models
Understand convolutional neural networks and vision transformers
Use PyTorch to train and fine-tune image classification models
Apply detection transformers for object detection and localization
Syllabus
3 lessons • 2 projects • 2 quizzesCertificate of completion available with Plus or Pro
Earn a certificate of completion and showcase your accomplishment on your resume or LinkedIn.
Projects in this course
- practice Project
Pet Image Classification and Detection with Transformers
Use transformers to fine-tune a vision transfomer (ViT) for image classification and evaluate an object detection model (e.g., DETR) on the Oxford-IIIT Pet Dataset. - practice Project
Classifying Microscopic Histopathology Images with PyTorch
Train and evaluate a CNN to detect tumors in histopathological scans from the PatchCamelyon dataset.
Meet the creator of the course
Heather Hardway
Principal Instructional Designer at CodecademyEarn a certificate of completion
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Reviews from learners
- The progress I have made since starting to use codecademy is immense! I can study for short periods or long periods at my own convenience - mostly late in the evenings.ChrisCodecademy Learner @ USA
- I felt like I learned months in a week. I love how Codecademy uses learning by practice and gives great challenges to help the learner to understand a new concept and subject.RodrigoCodecademy Learner @ UK
- Brilliant learning experience. Very interactive. Literally a game changer if you're learning on your own.John-AndrewCodecademy Learner @ USA
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Looking for something else?
Related resources
- Article
How do Vision Transformers Work? Architecture Explained
Learn how vision transformers (ViTs) work, their architecture, advantages, limitations, and how they compare to CNNs. - Article
PyTorch vs TensorFlow: Choosing the Best Framework for Deep Learning
Learn the differences between PyTorch and TensorFlow using examples and use cases. - Article
Getting Started with PyTorch Lightning: Build and Train Models
Learn how to use PyTorch Lightning for deep learning. This guide covers practical examples in model training, optimization, and distributed computing.
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Practice Projects
Guided projects that help you solidify the skills and concepts you're learning.Assessments
Auto-graded quizzes and immediate feedback help you reinforce your skills as you learn.Certificate of Completion
Earn a document to prove you've completed a course or path that you can share with your network.