Feature engineering for machine learning : principles and techniques for data scientists /

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Bibliographic Details
Main Authors: Zheng, Alice (Author), Casari, Amanda (Author)
Format: eBook
Published: Sebastopol, CA : O'Reilly Media, 2018.
Edition:First edition.
Online Access:CONNECT
Table of Contents:
  • The machine learning pipeline
  • Fancy tricks with simple numbers
  • Text data : flattening, filtering, and chunking
  • The effects of feature scaling : from bag-of-words to Tf-Idf
  • Categorical variables : counting eggs in the age of robotic chickens
  • Dimensionality reduction : squashing the data pancake with PCA
  • Nonlinear featurization via K-means model stacking
  • Automating the featurizer : image feature extraction and deep learning
  • Back to the feature : building an academic paper recommender
  • Linear modeling and linear algebra basics.