Generate Art

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prerequisites
basics of TensorFlow • basics of Keras • basics of scikit-learn
skills learned
mathematical operations on images • implementing loss functions • transfer learning
Rajeev Ratan
1 week · 8-12 hours per week · INTERMEDIATE
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Look inside
In this liveProject, you’ll replicate Google’s Deep Dream algorithm to explore the artistic creations of a neural network. You’ll start by investigating the latent space of a deep neural network and how manipulating its values can affect an input image. You’ll visualize inputs that maximize your filters, and manipulate these filters to produce ‘dream-like’ hallucinations.
This project is a part of the series Art Style Transfer with Deep Learning.
This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

Rajeev Ratan
Rajeev Ratan is a Principal AI Engineer and Data Scientist at BPP University in London, where he leads a data science team building agent-based systems, LLM products, and adaptive learning platforms. He has spent around 12 years in machine learning, much of it in computer vision, building real-time event detection for esports betting, object tracking and ReID for medical and warehousing systems, and deep learning for diamond identification at Kaithree Photonics, which he co-founded. He holds an MSc in AI from the University of Edinburgh, has four peer-reviewed publications, and has taught more than 70,000 learners through his Udemy courses on computer vision and AI. He also co-founded PyDataTT, Trinidad's leading Python community.

prerequisites

This liveProject is for intermediate Python programmers looking to enhance their data science skills with image manipulation techniques. To begin this liveProject, you will need to be familiar with:

TOOLS
  • Basics of TensorFlow
  • Basics of Keras
  • Basics of scikit-learn
  • Basics of Jupyter Notebook
TECHNIQUES
  • Basics of computer vision
  • Basics of deep learning
  • Basics of linear algebra

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