Название: Python 3 and Feature Engineering Автор: Oswald Campesato Издательство: Mercury Learning and Information Год: 2024 Страниц: 229 Язык: английский Формат: pdf (true) Размер: 10.7 MB
This book is designed for data scientists, machine learning practitioners, and anyone with a foundational understanding of Python 3.x. In the evolving field of data science, the ability to manipulate and understand datasets is crucial. The book offers content for mastering these skills using Python 3. The book provides a fast-paced introduction to a wealth of feature engineering concepts, equipping readers with the knowledge needed to transform raw data into meaningful information. Inside, you’ll find a detailed exploration of various types of data, methodologies for outlier detection using Scikit-Learn, strategies for robust data cleaning, and the intricacies of data wrangling. The book further explores feature selection, detailing methods for handling imbalanced datasets, and gives a practical overview of feature engineering, including scaling and extraction techniques necessary for different machine learning algorithms. It concludes with a treatment of dimensionality reduction, where you’ll navigate through complex concepts like PCA and various reduction techniques, with an emphasis on the powerful Scikit-Learn framework.
Features: - Includes numerous practical examples and partial code blocks that illuminate the path from theory to application - Explores everything from data cleaning to the subtleties of feature selection and extraction, covering a wide spectrum of feature engineering topics - Offers an appendix on working with the “awk” command-line utility - Features companion files available for downloading with source code, datasets, and figures.
What do i need to know for this book? A current knowledge of Python 3.x is useful because all the code samples are in Python. Knowledge of data structures will enable you to progress through the related chapters more quickly. The less technical knowledge that you have, the more diligence will be required in order to understand the various topics that are covered. If you want to be sure that you can grasp the material in this book, glance through some of the code samples to get an idea of how much is familiar to you and how much is new for you.
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Python 3 and Feature Engineering 
