P R.E S E N T S              .

Feature Engineering For Machine Learning

DATE: 2018-04-20  SIZE: 13.58 MB   DISKS: 2x 10MB     PAGES: n/a

PUBLISHER: O'Reilly Media                    GENRE:

AUTHOR: Alice Zheng, Amanda Casari

FORMAT: EPUB  PROTECTION: DRM  EDITION: n/a

URL: https://is.gd/H02GVa

LANGUAGE: English   ISBN: 9781491953242

: Feature engineering is a crucial step in the machine-learning pipeline, ye :
: this topic is rarely examined on its own. With this practical book, you'll :
: learn techniques for extracting and transforming features--the numeric     :
: representations of raw data--into formats for machine-learning models. Eac :
: chapter guides you through a single data problem, such as how to represent :
: text or image data. Together, these examples illustrate the main principle :
: of feature engineering. Rather than simply teach these principles, authors :
: Alice Zheng and Amanda Casari focus on practical application with exercise :
: throughout the book. The closing chapter brings everything together by     :
: tackling a real-world, structured dataset with several feature-engineering :
: techniques. Python packages including numpy, Pandas, Scikit-learn, and     :
: Matplotlib are used in code examples. You'll examine: Feature engineering  :
: for numeric data: filtering, binning, scaling, log transforms, and power   :
: transforms Natural text techniques: bag-of-words, n-grams, and phrase      :
: detection Frequency-based filtering and feature scaling for eliminating    :
: uninformative features Encoding techniques of categorical variables,       :
: including feature hashing and bin-counting Model-based feature engineering :
: with principal component analysis The concept of model stacking, using     :
: k-means as a featurization technique Image feature extraction with manual  :
: and deep-learning techniques                                               :

Looking for suppliers of quality Ebooks in any language!                  ::