Data science /
Pierson, Lillian,
Data science / Data science for dummies by Lillian Pierson ; foreword by Jake Porway, founder and executive director of DataKind. - 2nd ed. - xvi, 364 pages : illustrations, charts ; 24 cm.
Includes index.
Part 1: Getting Started with Data Science-----------
Part 2: Using Data Science to Extract Meaning from your Data------------
Part 3: Creating Data Visualization that Clearly Communicate Meaning------------
Part 4: Computing for Data Science------------
Part 5: Applying domain Expertise to solve Real World Problem using Data Science----------
Part 6: The Part of Tens--------------
Begins by explaining large data sets and data formats, including sample Python code for manipulating data. The book explains how to work with relational databases and unstructured data, including NoSQL. The book then moves into preparing data for analysis by cleaning it up or "munging" it. From there the book explains data visualization techniques and types of data sets. Part II of the book is all about supervised machine learning, including regression techniques and model validation techniques. Part III explains unsupervised machine learning, including clustering and recommendation engines. Part IV overviews big data processing, including MapReduce, Hadoop, Dremel, Storm, and Spark. The book finishes up with real world applications of data science and how data science fits into organizations.
9781119327639
2017932294
Information retrieval.
Data mining.
004 / PIE-D 2017 10285
Data science / Data science for dummies by Lillian Pierson ; foreword by Jake Porway, founder and executive director of DataKind. - 2nd ed. - xvi, 364 pages : illustrations, charts ; 24 cm.
Includes index.
Part 1: Getting Started with Data Science-----------
Part 2: Using Data Science to Extract Meaning from your Data------------
Part 3: Creating Data Visualization that Clearly Communicate Meaning------------
Part 4: Computing for Data Science------------
Part 5: Applying domain Expertise to solve Real World Problem using Data Science----------
Part 6: The Part of Tens--------------
Begins by explaining large data sets and data formats, including sample Python code for manipulating data. The book explains how to work with relational databases and unstructured data, including NoSQL. The book then moves into preparing data for analysis by cleaning it up or "munging" it. From there the book explains data visualization techniques and types of data sets. Part II of the book is all about supervised machine learning, including regression techniques and model validation techniques. Part III explains unsupervised machine learning, including clustering and recommendation engines. Part IV overviews big data processing, including MapReduce, Hadoop, Dremel, Storm, and Spark. The book finishes up with real world applications of data science and how data science fits into organizations.
9781119327639
2017932294
Information retrieval.
Data mining.
004 / PIE-D 2017 10285