Kennedy

Outlier Detection in Python, Kennedy B., 2025

Outlier Detection in Python, Kennedy B., 2025.
    
   Outliers—values that appear inconsistent with the rest of your data—can be the key to identifying fraud, performing a security audit, spotting hot activity, or just assessing the quality of a dataset. This unique guide introduces the outlier detection tools, techniques, and algorithms you’ll need to find, understand, and respond to the anomalies in your data.
Outlier Detection in Python illustrates the principles and practices of outlier detection with diverse real-world examples including social media, finance, network logs, and other important domains. You’ll explore a comprehensive set of statistical methods and machine learning approaches to identify and interpret the unexpected values in tabular, text, time series, and image data. Along the way, you’ll explore scikit-learn and PyOD, apply key OD algorithms, and add some high value techniques for real world OD scenarios to your toolkit.

Outlier Detection in Python, Kennedy B., 2025
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HTML the definitive guide, Musciano С., Kennedy B., 1998

HTML the definitive guide, Musciano С., Kennedy B., 1998.

   Learning Hypertext Markup Language - most commonly known by its acronym, HTML - is like learning any new language, computer or human. Most students first immerse themselves in examples. Think how adept you'd become if Mom, Dad. your brothers and sisters all spoke fluent HTML. Studying others is a natural way to learn, making learning easy and fun. Our advice to anyone wanting to learn HTML is to get out there on the World Wide Web with a suitable browser and see for yourself what looks good, what's effective, what works for you. Examine others HTML source files and ponder the possibilities. Mimicry is how many of the current webmasters have learned the language.

HTML the definitive guide, Musciano С., Kennedy B., 1998

Скачать и читать HTML the definitive guide, Musciano С., Kennedy B., 1998