Using PyTorch for Image Classification and Object Detection

Gain insights into using PyTorch for image classification and detection, delve into model implementation, and explore deployment on edge devices with ONNX and OpenVINO.

Intermediate

46 Lessons

Certificate of Completion

Gain insights into using PyTorch for image classification and detection, delve into model implementation, and explore deployment on edge devices with ONNX and OpenVINO.

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

17 Playgrounds

7 Quizzes

This course includes

17 Playgrounds

7 Quizzes

Course Overview

Image classification and object detection have gained widespread use in recent years. Content categorization and monitoring, disease diagnosis from medical images, identifying terrain in satellite images, and detecting road elements for self-driving cars are classification problems at their core. PyTorch is a popular framework for these tasks—offering a useful mix of user-friendliness, deep learning functionalities, customization, and optimization. In this course, you will cover the fundamentals of classif...Show More

What You'll Learn

An understanding of core concepts related to image classification, object detection, and convolutional neural networks

Hands-on experience using image classification architectures

Familiarity with PyTorch for image classification tasks

Working knowledge of ONNX and OpenVINO for deploying deep learning models

What You'll Learn

An understanding of core concepts related to image classification, object detection, and convolutional neural networks

Course Content

Before We Start

Get familiar with image classification, object detection, and neural network basics with PyTorch.

Introduction to the Course

Image Classification vs. Object Detection

Basics of Neural Networks

Basics of Convolutional Neural Networks

Grasp the fundamentals of CNNs, including convolution operations, pooling, and batch normalization.

Introduction to the Basics of CNNs What is 2D Convolution?Images and Filters Convolutional Neural Networks Quiz on the Basics of CNNs

Cats vs Dogs Classification with Convolutional Neural Networks

Project

Popular Neural Network Architectures for Image Classification

Examine various neural network architectures for image classification, highlighting key advancements and efficiencies.

Introduction to Architectures for Image Classification AlexNet (2012)VGG16 (2014)InceptionV1—GoogleNet (2014)ResNet (2015)MobileNetV1 (2017) and MobileNetV2 (2018)EfficientNet (2019)Image Classification Architectures Summary Quiz on the Basics of CNNs and their Architectures

Using PyTorch for Image Classification

Grasp the fundamentals of using PyTorch for efficient image classification and model fine-tuning.

Introduction to PyTorch for Image Classification Data Preparation Training a Custom Model from Scratch Using PyTorch Fine-Tuning Models Transfer Learning Quiz on Training Issues and Fine-Tuning

Model Deployment

Solve problems in deploying and optimizing AI models across various hardware frameworks and platforms.

Introduction to Model Deployment Using Deployment Frameworks with PyTorch

Using a PyTorch Model in JavaScript with ONNX

Project

Basics of Object Detection

3 Lessons

Tackle object detection's complexities and distinguish between one-stage and two-stage architectures.

Two-Stage Object Detection Architectures

5 Lessons

Build on two-stage object detection advancements with R-CNN, Fast R-CNN, and Faster R-CNN.

One-Stage Object Detection Architectures

7 Lessons

Step through one-stage object detection architectures focusing on YOLO and SSD models.

YOLOv7 Model Train and Inference on Edge

4 Lessons

Get started with training, deploying, and optimizing the YOLOv7 model for edge devices.

10.

Conclusion

1 Lesson

Break apart key strategies for using PyTorch in image classification and object detection.

11.

Appendix

1 Lesson

Break down complex ideas for managing Python environments with Anaconda.

Building a System for Safety Helmet Detection Based on YOLOv5

Project

Course Author

Trusted by 1.4 million developers working at companies

Anthony Walker

@_webarchitect_

Emma Bostian 🐞

@EmmaBostian

Evan Dunbar

ML Engineer

Carlos Matias La Borde

Software Developer

Souvik Kundu

Front-end Developer

Vinay Krishnaiah

Software Developer

Eric Downs

Musician/Entrepeneur

Kenan Eyvazov

DevOps Engineer

Anthony Walker

@_webarchitect_

Emma Bostian 🐞

@EmmaBostian

Hands-on Learning Powered by AI

See how Educative uses AI to make your learning more immersive than ever before.

Instant Code Feedback

Evaluate and debug your code with the click of a button. Get real-time feedback on test cases, including time and space complexity of your solutions.

AI-Powered Mock Interviews

Put your skills to the test in a simulated interview setting. Receive personalized feedback based on your performance. Available in Premium & Premium Plus plans.

Adaptive Learning

At various checkpoints throughout Educative courses, you will be prompted to take a quick assessment. Receive a condensed curriculum tailored to your strengths and skill gaps.

Explain with AI

Select any text within any Educative course, and get an instant explanation — without ever leaving your browser.

AI Code Mentor

AI Code Mentor helps you quickly identify errors in your code, learn from your mistakes, and nudge you in the right direction — just like a 1:1 tutor!