Machine Learning Pocket Reference: Working with Structured Data in Python
With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project. Ideal for programmers, data scientists, and AI engineers, this book includes an overview of the machine learning process and walks you through classification with structured data. You'll also learn methods for clustering, predicting a continuous value (regression), and reducing dimensionality, among other topics. This pocket reference includes sections that cover: Classification, using the Titanic dataset Cleaning data and dealing with missing data Exploratory data analysis Common preprocessing steps using sample data Selecting features useful to the model Model selection Metrics and classification evaluation Regression examples using k-nearest neighbor, decision trees, boosting, and more Metrics for regression evaluation Clustering Dimensionality reduction Scikit-learn pipelines
yazar | Matt Harrison |
---|---|
Boyutlar ve boyutlar | 11,4 x 1,9 x 17,8 cm |
Tarafından yayınlandı | 10 Eylül 2019 |
ERWIN N GRISWOLD 18,9 x 0,2 x 24,6 cm 18,9 x 0,4 x 24,6 cm 1 Ocak 2017 18,9 x 0,3 x 24,6 cm 18,9 x 0,5 x 24,6 cm 18,9 x 0,6 x 24,6 cm 30 Ekim 2011 3 Ocak 2017 Additional Contributors 15 x 0,5 x 22 cm WADE H MCCREE 28 Ekim 2011 28 Şubat 2018 ROBERT H BORK 29 Ekim 2011 Mdpi AG Kolektif
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Sürüm ayrıntıları
yazar | Matt Harrison |
---|---|
isbn 10 | 1492047546 |
isbn 13 | 978-1492047544 |
Yayımcı | O′Reilly; Revised. baskı |
Dilim | İngilizce |
Boyutlar ve boyutlar | 11,4 x 1,9 x 17,8 cm |
Tarafından yayınlandı Machine Learning Pocket Reference: Working with Structured Data in Python | 10 Eylül 2019 |
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