Automate Pipeline

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prerequisites
basic Python, pandas, Matplotlib, NumPy, SciPy, scikit-learn, and deep learning/Keras
skills learned
implementing AutoML using the automated data preprocessing API and AutoKeras Task API • customizing sequential and graph-structured AutoML pipelines
Xiaotian Han
1 week · 4-6 hours per week · INTERMEDIATE
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catalog / Data Science / Machine Learning
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In this liveProject, you’ll implement an AutoML pipeline using the AutoKeras functional API. You’ll make use of the built-in blocks in AutoKeras to conduct automated hyperparameter tuning and model selection for creating an image classification model. Your challenges will include customizing both a sequential AutoML pipeline, and customizing graph-structured AutoML 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 AutoKeras

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