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Scikit-learn Advanced Features | Data Science
It demonstrates some useful scikit-learn concepts in transforming features, pipelining, grid search, and much more.
machine-learning scikit-learn data-science feature-engineering
Automatic extraction of relevant features from time series.
time-series feature-engineering library code
Neural Network Intelligence (NNI)
NNI is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture Search, Hyperparameter Tuning and Model ...
automl neural-architecture-search model-compression feature-engineering
Kick Assist
An Interactive Dashboard enabling users to make data-driven decisions about their Kickstarter campaign to maximize the probability for successful funding
data-science interpretability scraping xgboost
Audio signal analysis and Feature extraction
Extract features from audio signal as a part of Speech recognition task
speech-recognition audio feature-engineering melspectrum
Feature importance
A python source file illustrating multiple methods to extract Feature importance from a dataset
feature-engineering feature-importance feature-selection data-science
The Process for Data Preparation and Feature Engineering
To get our predictions right, we must construct the data set and transform the data correctly.
data-collection feature-engineering systems-design tutorial
Attributed Social Network Embedding
A sparsity aware and memory efficient implementation of "Attributed Social Network Embedding" (TKDE 2018).
deep-learning graph-convolutional-networks graph-embedding representation-learning
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