Data Science Foundations: Data Mining in Python.
(Online Course)

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Published
Carpenteria, CA linkedin.com, 2021.
Format
Online Course
Status

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Language
English

Notes

General Note
3/26/202112:00:00AM
Participants/Performers
Presenter: Barton Poulson
Description
Learn the key concepts and skills behind one of the most important elements of data science: data mining.
Description
Data mining is the area of data science that focuses on finding actionable patterns in large and diverse datasets: clusters of similar customers, trends over time that can only be spotted after disentangling seasonal and random effects, and new methods for predicting important outcomes. In this course, instructor Barton Poulson introduces you to data mining that uses the programming language Python. Barton goes over some preliminaries, such as the tools you may use for data mining. He discusses aspects of dimensionality reduction, then explains clustering, including hierarchical clustering, k-Means, DBSCAN, and more. Barton covers classification, including kNN and decision trees. He goes into association analysis and introduces you to Apriori, Eclat, and FP-Growth. Barton steps you through a time-series decomposition, then concludes with sentiment scoring and other text mining tools.
System Details
Latest version of the following browsers: Chrome, Safari, Firefox, or Internet Explorer. Adobe Flash Player Plugin. JavaScript and cookies must be enabled. A broadband Internet connection.

Citations

APA Citation, 7th Edition (style guide)

Poulson, B. (2021). Data Science Foundations: Data Mining in Python . linkedin.com.

Chicago / Turabian - Author Date Citation, 17th Edition (style guide)

Poulson, Barton. 2021. Data Science Foundations: Data Mining in Python. linkedin.com.

Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)

Poulson, Barton. Data Science Foundations: Data Mining in Python linkedin.com, 2021.

MLA Citation, 9th Edition (style guide)

Poulson, Barton. Data Science Foundations: Data Mining in Python linkedin.com, 2021.

Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.