Lecture 3 - Image classification

Teacher: Mohit VAISHNAV (ANITI)

Lecture video

View the recorded lecture here (this will only be available for approximately 6 weeks after the course)

Contents

• Motivation
• Framework for classification
  • Overview
  • Challenges
  • Pipeline
• Receptive field and convolutions
• Datasets
• Models of classification
  • Pre alexnet
  • Post alexnet
• Trends in deep learning (if time permits)

Notes

Link to slide

Tutorial Notebook

Writing a toy model for CALTECH classification and other variant (pretrained network)

Writing a toy model for MNIST classification

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