Author: Mark Fenner

Brand: PEARSON EDUCATION

Color: Blue

Edition: First Edition

Binding: paperback

Number Of Pages: 504

Release Date: 15-02-2020

Details: Students are crushing to master powerful machine learning techniques for improving decision-making and scaling analysis to immense datasets. Machine learning with Python for everyone brings together all they'll need to succeed: a practical understanding of the machine learning process, accessible code, skills for implementing that process with Python and the scikit-learn library, and real expertise in using learning systems intelligently.Reflecting 20 years of experience teaching non-specialists, the author teaches through carefully-crafted datasets that are complex enough to be interesting, but simple enough for non-specialists. Building on this foundation, the book presents real-world case studies that apply his lessons in detailed, nuanced ways. Throughout, he offers clear narratives, practical “code-alongs,” and easy-to-understand images -- focusing on Mathematics only where it’s necessary to make connection and deepen insight.
table of Contents:
Chapter 1: Let’s discuss learning
Chapter 2: predicting categories: getting started with classification
Chapter 3: predicting numerical values: getting started with regression
Chapter 4: evaluating and comparing learners
Chapter 5: evaluating classifiers
Chapter 6: evaluating Regressors
Chapter 7: more classification methods
Chapter 8: more regression methods
Chapter 9: manual feature engineering: manipulating data for fun and Profit
Chapter 10: models that engineer features for us
Chapter 11: feature engineering for domains: domain-specific learning online chapters
Chapter 12: tuning hyperparameters and pipelines
Chapter 13: combining learners
Chapter 14: connecting, extensions, and further directions

EAN: 9789353944902

Package Dimensions: 9.9 x 8.0 x 1.1 inches

Languages: English