Data Simplification: Taming Information With Open Source Tools
addresses the simple fact that modern data is too big and complex
to analyze in its native form. Data simplification is the process
whereby large and complex data is rendered usable. Complex data
must be simplified before it can be analyzed, but the process of
data simplification is anything but simple, requiring a specialized
set of skills and tools. This book provides data scientists from
every scientific discipline with the methods and tools to simplify
their data for immediate analysis or long-term storage in a form
that can be readily repurposed or integrated with other data.
Drawing upon years of practical experience, and using numerous
examples and use cases, Jules Berman discusses the principles,
methods, and tools that must be studied and mastered to achieve
data simplification, open source tools, free utilities and snippets
of code that can be reused and repurposed to simplify data, natural
language processing and machine translation as a tool to simplify
data, and data summarization and visualization and the role they
play in making data useful for the end user.
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