Transformers for Computer Vision Applications

This course covers transformer networks in computer vision, from basics to advanced applications, focusing on attention mechanisms and Python libraries.

Advanced

36 Lessons

Certificate of Completion

This course covers transformer networks in computer vision, from basics to advanced applications, focusing on attention mechanisms and Python libraries.

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This course includes

3 Projects

24 Playgrounds

8 Quizzes

This course includes

3 Projects

24 Playgrounds

8 Quizzes

Course Overview

This is a comprehensive course on transformer networks and their use cases in computer vision. You’ll begin by exploring the rise of transformers and attention mechanisms and their role in deep neural networks. You’ll gain insights into self-attention mechanisms, multihead attention, and the pros and cons of transformers building a strong foundation. Next, you’ll discover how transformers reshape image analysis. Comparing self-attention with convolutional encoders and understanding spatial vs. channel vs. ...Show More

What You'll Learn

An understanding of transformers and attention mechanisms

Hands-on implementation of computer vision techniques with transformer models

The ability to apply transfer learning for image classification

A strong grasp of object detection and segmentation using transformers

What You'll Learn

An understanding of transformers and attention mechanisms

Course Content

Introduction

This course offers a comprehensive exploration of transformers in computer vision.

Introduction to the Course

Overview of Transformer Networks

This chapter focuses on the transformers, attention mechanisms, self, multihead, encoder-decoder attention, and unsupervised/self-supervised pretraining

Introduction to Transformers

The Rise of Transformers

Inductive Bias in DNNs

Attention: General Deep Learning Idea

Attention in NLP

Is Attention All We Need?

Quiz: Attention and Inductive Bias

Self-Attention Mechanism

Self-Attention Matrix Equations

Multihead Attention

Encoder-Decoder Attention

Transformers Pros and Cons

Unsupervised and Self-Supervised Pretraining

Quiz: Transformers and Multihead Attention

Neural Machine Translation with a Transformer and Keras

Project

Transformers in Computer Vision

This chapter focuses on transformers in computer vision, covering encoder-decoder patterns and attention types and comparing self-attention with convolution.

Introduction to Transformers in Computer Vision

Encoder-Decoder Design Pattern

Convolutional Encoders

Self-Attention vs. Convolution

Quiz: Encoder-Decoder Architecture and Attention Mechanism in Computer Vision

Spatial vs. Channel vs. Temporal Attention

Local vs. Global Attention

Pros and Cons of Attention in CV

Quiz: Attention in Computer Vision

Transformers in Image Classification

This chapter focuses on image classification with vision transformers (ViT, DeiT) and shifter window (Swin) transformers.

Image Classification with Vision Transformer (ViT and DeiT)

Shifter Window (Swin) Transformers

Quiz: Transformers in Image Classification

Fine-Tuning Vision Transformers for Image Classification

Project

Transformers in Object Detection

In this chapter, you’ll cover methods used for object detection, focusing on DEtection TRansformers (DETR).

Object Detection Methods Review

DEtection TRansformers (DETR)

Quiz: Transformers in Object Detection

Transformers in Semantic Segmentation

3 Lessons

This chapter focuses on image segmentation techniques using ConvNets and transformers, highlighting their differences and applications.

Spatio-Temporal Transformers

2 Lessons

In this chapter, you’ll cover spatio-temporal transformers for video action recognition using Python, focusing on video classification tasks.

Object Detection with Vision Transformers

Project

Wrap Up

1 Lesson

This chapter summarizes key takeaways, covering attention mechanisms, transformers in NLP and computer vision, and extending to video analysis.

Course Author

Trusted by 1.4 million developers working at companies

Anthony Walker

@_webarchitect_

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

Souvik Kundu

Front-end Developer

Eric Downs

Musician/Entrepeneur

Anthony Walker

@_webarchitect_

Evan Dunbar

ML Engineer

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