Details zum E-Book

scikit-learn Cookbook. Over 80 recipes for machine learning in Python with scikit-learn - Second Edition

scikit-learn Cookbook. Over 80 recipes for machine learning in Python with scikit-learn - Second Edition

Julian Avila, Trent Hauck

E-book
Python is quickly becoming the go-to language for analysts and data scientists due to its simplicity and flexibility, and within the Python data space, scikit-learn is the unequivocal choice for machine learning. This book includes walk throughs and solutions to the common as well as the not-so-common problems in machine learning, and how scikit-learn can be leveraged to perform various machine learning tasks effectively.

The second edition begins with taking you through recipes on evaluating the statistical properties of data and generates synthetic data for machine learning modelling. As you progress through the chapters, you will comes across recipes that will teach you to implement techniques like data pre-processing, linear regression, logistic regression, K-NN, Naïve Bayes, classification, decision trees, Ensembles and much more. Furthermore, you’ll learn to optimize your models with multi-class classification, cross validation, model evaluation and dive deeper in to implementing deep learning with scikit-learn. Along with covering the enhanced features on model section, API and new features like classifiers, regressors and estimators the book also contains recipes on evaluating and fine-tuning the performance of your model.

By the end of this book, you will have explored plethora of features offered by scikit-learn for Python to solve any machine learning problem you come across.
  • 1. High-Performance Machine Learning: Numpy
  • 2. Premodel Workflow & Preprocessing
  • 3. Dimensionality Reduction
  • 4. Linear Models with scikit-learn
  • 5. Linear Models: Logistic Regression
  • 6. Building Models with Distance Metrics
  • 7. Cross-Validation & Post Model Workflow
  • 8. Support Vector Machines
  • 9. Tree Algorithms and Ensembles
  • 10. Text and Multi-Class Classification with scikit-learn
  • 11. Neural Networks
  • 12. Create a Simple Estimator
  • Titel: scikit-learn Cookbook. Over 80 recipes for machine learning in Python with scikit-learn - Second Edition
  • Autor: Julian Avila, Trent Hauck
  • Originaler Titel: scikit-learn Cookbook. Over 80 recipes for machine learning in Python with scikit-learn - Second Edition
  • ISBN: 9781787289833, 9781787289833
  • Veröffentlichungsdatum: 2017-11-16
  • Format: E-book
  • Artikelkennung: e_15si
  • Verleger: Packt Publishing