Crystal Ball Instruction Manual

Format:

Book

Author/Creator:

Davies, Stephen, author.

Language:

English

Subjects (All):

Computer science--Textbooks.

Computer science.

Mathematics--Textbooks.

Mathematics.

Physical Description:

1 online resource

Place of Publication:

[Place of publication not identified] University of Mary Washington 2024.

Language Note:

In English.

Summary:

Welcome to Volume Two of the Crystal Ball series: Foundations for Data Science! I titled the first volume “Introduction to Data Science” because it led you through a dip-your-toes-in-the-water experience. You took a brief tour through the various elements in this diverse field and got a feel for what it was all about. Since you’re still reading, this means you’re still interested, and ready to explore the next level. In Foundations, we’ll solidify your growing knowledge so that you have a firm base on which to build everything else. Future volumes in this series will cover applications, advanced techniques, and some special data types that require special treatment. But it all ultimately rests on the skill set you’ll have built in Volumes One and Two of this series.

Contents:

Intermission and review

Navigating the Spyder’s web

EDA: review and extensions

KDEs and distributions

Random value generation

Synthetic data sets

JSON (1 of 2)

JSON (2 of 2)

LOWESS

Data fusion

Long, wide, and “tidy” data

Dates and times

Using logarithms

Accessing databases

Screen scraping (1 of 2)

Screen scraping (2 of 2)

Probabilistic reasoning

Causality

Naïve Bayes (1 of 3)

Naïve Bayes (2 of 3)

Naïve Bayes (3 of 3)

APIs

kNN (1 of 2)

kNN (2 of 2)

Two key ML principles

Feature selection

Association Analysis

“Special” data types

Notes:

Description based on online resource