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Deep Learning for Multimodal Image Retrieval

prerequisites
intermediate Python • beginner PyTorch • basic neural networks, computer vision, and natural language processing
skills learned
train a Word2vec word representation method • train a CNN with PyTorch • compute similarities between words and images
Raul Gomez
3 weeks · 8-10 hours per week · ADVANCED

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Have you ever spent too long scrolling through your photos to find that one picture you know you took? In this liveProject, you’ll solve that problem—with the power of deep learning!

Your challenge is to create a working image retrieval system that can search images based on text queries: type in ‘dog’ and you’ll get pictures of dogs. You’ll combine cutting-edge natural language processing and computer vision techniques, exploit semantic word representation methods, and train a neural network on social media data using image captions as annotations. This liveProject will develop your skills with PyTorch, and be an impressive piece for your data science portfolio.
This project is designed for learning purposes and is not a complete, production-ready application or solution.

book resources

When you start your liveProject, you get full access to the following books for 90 days.

project author

Raul Gomez
Raúl Gómez studied telecommunications engineering at UPC and did a computer vision master at UAB (Computer Vision Center), followed by a PhD. He has published in top computer vision conferences and runs a popular blog where he disseminates his research and writes about general machine learning topics (gombru.github.io).

prerequisites

This liveProject is for accomplished (intermediate) Python programmers who have developed basic neural networks and are comfortable setting up a training environment for machine learning. To begin this liveProject you will need to be familiar with:

TOOLS
  • Intermediate Python
  • Beginner PyTorch
TECHNIQUES
  • Basics of machine learning
  • Basics of computer vision
  • Basics of natural language processing
  • Basics of neural networks
  • Setting up a neural network training environment

you will learn

In this liveProject, you’ll learn how to extend deep concepts to both natural language processing and computer vision. You’ll develop experience with both PyTorch and deep learning libraries, and extend them to achieve nonstandard tasks.

  • Train a Word2Vec word representation method with custom data
  • Customize and train a CNN with PyTorch
  • Compute similarities between words and images given their embeddings

features

Self-paced
You choose the schedule and decide how much time to invest as you build your project.
Project roadmap
Each project is divided into several achievable steps.
Get Help
While within the liveProject platform, get help from other participants and our expert mentors.
Compare with others
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book resources
Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.
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