Practicing Data Science

Written by Rosaria Silipo
data-science-case-studies-knime

A Collection of Data Science Case Studies

There are many declinations of data science projects: with or without labeled data; stopping at data wrangling or involving machine learning algorithms; predicting classes or predicting numbers; with unevenly distributed classes, with binary classes, or even with no examples of one of the classes; with structured data and with unstructured data; using past samples or just remaining in the present; with real time or close to real time execution requirements and with acceptably slower performances; showing the results in shiny reports or hiding the nitty and gritty behind a neutral IT architecture; and - last but not least - with large budgets or no budget at all.

In the course of my professional life, I have seen many of the above projects and their data science nuances. So much experience - and the inevitably of related mistakes - should not be lost. Therefore the idea of this book: a collection of data science case studies from past projects.

This book includes data science case studies from IoT, financial industry, customer intelligence, social media, cybersecurity, and more.

Download free sample chapter of Practicing Data Science.

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