Customize AutoKeras Blocks

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prerequisites
basic Python, pandas, Matplotlib, NumPy, SciPy, scikit-learn, and deep learning/Keras
skills learned
customizing an AutoKeras block for CIFAR-10 image classification • designing a hyperblock for model selection
Xiaotian Han
1 week · 4-6 hours per week · INTERMEDIATE
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catalog / Data Science
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Look inside

In this liveProject, you’ll build an AutoKeras block for image classification to help tune a neural network and customize the search space. You’ll then combine the block you have created with other prebuilt AutoKeras blocks to put together a complete automated machine learning pipeline.

This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

Xiaotian Han
Xiaotian Han is a PhD student at Texas A&M University, where he works in the field of data mining and automated machine learning. He has published several research papers related to data mining and automated machine learning and participated in an open-source package, AutoRec, which is highly based on the AutoKeras.

prerequisites

This liveProject is for Python programmers who know the basics of deep learning. To begin this liveProject, you will need to be familiar with the following:


TOOLS
  • Basic Python
  • Basic pandas
  • Basic Matplotlib
  • Basic NumPy
  • Basic SciPy
  • Basic scikit-learn
TECHNIQUES
  • Basic deep learning/Keras
  • Basics of image data processing

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