Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists

Buy

Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. Each chapter guides you through a single data problem, such as how to represent text or image data. Together, these examples illustrate the main principles of feature engineering.

Rather than simply teach these principles, authors Alice Zheng and Amanda Casari focus on practical application with exercises throughout the book. The closing chapter brings everything together by tackling a real-world, structured dataset with several feature-engineering techniques. Python packages including numpy, Pandas, Scikit-learn, and Matplotlib are used in code examples.

You’ll examine:

  • Feature engineering for numeric data: filtering, binning, scaling, log transforms, and power transforms
  • Natural text techniques: bag-of-words, n-grams, and phrase detection
  • Frequency-based filtering and feature scaling for eliminating uninformative features
  • Encoding techniques of categorical variables, including feature hashing and bin-counting
  • Model-based feature engineering with principal component analysis
  • The concept of model stacking, using k-means as a featurization technique
  • Image feature extraction with manual and deep-learning techniques
(HTML tags aren't allowed.)

Applied Text Analysis with Python: Enabling Language-Aware Data Products with Machine Learning
Applied Text Analysis with Python: Enabling Language-Aware Data Products with Machine Learning

From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural...

Scientific Computing with Python 3
Scientific Computing with Python 3

Key Features

  • Your ultimate resource for getting up and running with Python numerical computations
  • Explore numerical computing and mathematical libraries using Python 3.x code with SciPy and NumPy modules
  • A hands-on guide to implementing mathematics with Python, with complete...
Machine Learning and Security: Protecting Systems with Data and Algorithms
Machine Learning and Security: Protecting Systems with Data and Algorithms

Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you’ll explore ways to apply machine learning to security...


Python Web Scraping: Hands-on data scraping and crawling using PyQT, Selnium, HTML and Python, 2nd Edition
Python Web Scraping: Hands-on data scraping and crawling using PyQT, Selnium, HTML and Python, 2nd Edition

Successfully scrape data from any website with the power of Python 3.x

Key Features

  • A hands-on guide to web scraping using Python with solutions to real-world problems
  • Create a number of different web scrapers in Python to extract information
  • This book...
Artificial Intelligence: Structures and Strategies for Complex Problem Solving (5th Edition)
Artificial Intelligence: Structures and Strategies for Complex Problem Solving (5th Edition)
Can machines think like people? This question is the driving force behind Artificial Intelligence, but it is only the starting point of this ever-evolving, exciting discipline. AI uses different strategies to solve the complex problems that arise wherever computer technology is applied, from those areas pertaining to perception and adaptation...
Mastering .NET Machine Learning
Mastering .NET Machine Learning

About This Book

  • Based on .NET framework 4.6.1, includes examples on ASP.NET Core 1.0
  • Set up your business application to start using machine learning techniques
  • Familiarize the user with some of the more common .NET libraries for machine learning
  • Implement...
©2019 LearnIT (support@pdfchm.net) - Privacy Policy