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 designed for learning purposes and is not a complete, production-ready application or solution.
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project author
Rajeev Ratan
Rajeev Ratan is a data scientist, computer vision consultant, and researcher. He has spent the last five years working at several computer vision startups, and has created several popular online courses on OpenCV and deep learning convolutional neural networks. He holds an MSc in Artificial Intelligence from the University of Edinburgh and has published research on using data-driven methods for Probabilistic Stochastic Modeling for Public Transport.
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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