Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists by Alice Zheng, Amanda Casari

Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists Alice Zheng, Amanda Casari ebook
Publisher: O'Reilly Media, Incorporated
Format: pdf
ISBN: 9781491953242
Page: 214

Auflage, Cambridge University Press, Cambridge ( ISBN: 978-1107057135). Graphical Models and Bayesian Networks. Classification, regression, and clustering). Since most Machine Learning books discuss very little feature engineering you're better off reading books that are domain specific and more or less related to the problem you're trying to solve. The Data Science and Engineering with Spark XSeries, created in partnership with Databricks, will teach students how to perform data science and dataengineering at scale using Spark, a cluster computing system well-suited for large-scale machine learning tasks. Basic knowledge of machine learning techniques (i.e. (2014) Understanding Machine Learning: From Theory to Algorithms. In this one-day introductory training, you will gain practical experience in the latest Analytics and Data Science technology and techniques. Feature Engineering for Machine Learning and Data Analytics provides a comprehensive introduction to feature engineering, including feature generation,feature extraction, feature transformation, feature selection, and feature analysis and evaluation. Simple : feature engineering is what will determine if your project is going to success, not only how good you are on statistical or computer techniques. What is Feature Engineering (FE)?. Understand machine learning principles (training, validation, etc. Machine Learning and Data Science. Shalev-Shwartz, S.; Ben-David, S. A very good definition, elegant in its simplicity, is that feature engineering is the process to create features that make machine learning algorithms work. ) Knowledge of data query and data processing tools (i.e. Mastering Feature Engineering: Principles and Techniques for Data Scientists. Of Winder Research, for an intensive 3-day Data science and Analytics course, that will leave you with practical tools for utilizing Machine Learning principles in your organisation. (2018) Feature Engineering forMachine Learning Models: Principles and Techniques for Data Scientists. Become a Data Analytics expert in 10 weeks.