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The Building Data Genome ProjectA collection of non-residential buildings for performance analysis and algorithm benchmarking
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Amazing Feature EngineeringFeature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.
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Kaggle CompetitionsThere are plenty of courses and tutorials that can help you learn machine learning from scratch but here in GitHub, I want to solve some Kaggle competitions as a comprehensive workflow with python packages. After reading, you can use this workflow to solve other real problems and use it as a template.
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BlurrData transformations for the ML era
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Feature Engineering And Feature SelectionA Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
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NniAn open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
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Awesome Feature EngineeringA curated list of resources dedicated to Feature Engineering Techniques for Machine Learning
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