(EBook PDF) Data simplification taming information with open source tools 1st Edition by Jules Berman 0128038543 9780128037812 9780128038543 full chapters

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Product details:

ISBN-10 : 0128038543

ISBN-13 : 9780128037812, 9780128038543

Author : Jules J. Berman 

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.

 

Data simplification : taming information with open source tools 1st Table of contents:

Chapter 1: The Simple Life
Abstract
1.1 Simplification Drives Scientific Progress
1.2 The Human Mind is a Simplifying Machine
1.3 Simplification in Nature
1.4 The Complexity Barrier
1.5 Getting Ready
Open Source Tools
Glossary
Chapter 2: Structuring Text
Abstract
2.1 The Meaninglessness of Free Text
2.2 Sorting Text, the Impossible Dream
2.3 Sentence Parsing
2.4 Abbreviations
2.5 Annotation and the Simple Science of Metadata
2.6 Specifications Good, Standards Bad
Open Source Tools
Glossary
Chapter 3: Indexing Text
Abstract
3.1 How Data Scientists Use Indexes
3.2 Concordances and Indexed Lists
3.3 Term Extraction and Simple Indexes
3.4 Autoencoding and Indexing with Nomenclatures
3.5 Computational Operations on Indexes
Open Source Tools
Glossary
Chapter 4: Understanding Your Data
Abstract
4.1 Ranges and Outliers
4.2 Simple Statistical Descriptors
4.3 Retrieving Image Information
4.4 Data Profiling
4.5 Reducing Data
Open Source Tools
Glossary
Chapter 5: Identifying and Deidentifying Data
Abstract
5.1 Unique Identifiers
5.2 Poor Identifiers, Horrific Consequences
5.3 Deidentifiers and Reidentifiers
5.4 Data Scrubbing
5.5 Data Encryption and Authentication
5.6 Timestamps, Signatures, and Event Identifiers
Open Source Tools
Glossary
Chapter 6: Giving Meaning to Data
Abstract
6.1 Meaning and Triples
6.2 Driving Down Complexity with Classifications
6.3 Driving Up Complexity With Ontologies
6.4 The Unreasonable Effectiveness of Classifications
6.5 Properties That Cross Multiple Classes
Open Source Tools
Glossary
Chapter 7: Object-Oriented Data
Abstract
7.1 The Importance of Self-Explaining Data
7.2 Introspection and Reflection
7.3 Object-Oriented Data Objects
7.4 Working with Object-Oriented Data
Open Source Tools
Glossary
Chapter 8: Problem Simplification
Abstract
8.1 Random Numbers
8.2 Monte Carlo Simulations
8.3 Resampling and Permutating
8.4 Verification, Validation, and Reanalysis
8.5 Data Permanence and Data Immutability

 

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