Data Science Foundations: Data Mining in Python

Focused View

Barton Poulson

3:03:47

0 View

01 Introduction

001 Python for data mining.mp4

00:37

002 What you should know.mp4

00:45

003 Exercise files.mp4

00:40

02 Preliminaries

001 Tools for data mining.mp4

06:06

002 The CRISP-DM data mining model.mp4

03:20

003 Privacy copyright and bias.mp4

04:26

004 Validating results.mp4

06:15

03 Dimensionality Reduction

001 Dimensionality reduction overview.mp4

06:35

002 Handwritten digits dataset.mp4

05:06

003 PCA.mp4

03:57

004 LDA.mp4

03:50

005 t-SNE.mp4

04:21

006 Challenge PCA.mp4

01:41

007 Solution PCA.mp4

01:57

04 Clustering

001 Clustering overview.mp4

06:53

002 Penguin dataset.mp4

02:44

003 Hierarchical clustering.mp4

03:08

004 K-means.mp4

05:36

005 DBSCAN.mp4

04:12

006 Challenge K-means.mp4

01:12

007 Solution K-means.mp4

02:43

05 Classification

001 Classification overview.mp4

06:10

002 Spambase dataset.mp4

03:34

003 KNN.mp4

04:42

004 Naive Bayes.mp4

03:08

005 Decision trees.mp4

03:27

006 Challenge KNN.mp4

02:11

007 Solution KNN.mp4

03:22

06 Association Analysis

001 Association analysis overview.mp4

05:54

002 Groceries dataset.mp4

01:57

003 Apriori.mp4

04:58

004 Eclat.mp4

04:20

005 FP-Growth.mp4

03:36

006 Challenge Apriori.mp4

01:33

007 Solution Apriori.mp4

03:17

07 Time-Series Mining

001 Time-series mining.mp4

04:23

002 Air Passengers dataset.mp4

02:31

003 Time-Series decomposition.mp4

04:14

004 ARIMA.mp4

07:56

005 MLP.mp4

05:12

006 Challenge Decomposition.mp4

02:11

007 Solution Decomposition.mp4

02:33

08 Text Mining

001 Text mining overview.mp4

04:34

002 Iliad dataset.mp4

01:10

003 Sentiment analysis Binary classification.mp4

05:04

004 Sentiment analysis Sentiment scoring.mp4

04:24

005 Word pairs.mp4

04:28

006 Challenge Sentiment scoring.mp4

01:05

007 Solution Sentiment scoring.mp4

03:13

09 Conclusion

001 Next steps.mp4

02:36

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.

More details

User Reviews

Rating

average 0

Total votes0

Focused display

Python

Data Science

Data Mining

Barton Poulson

Instructor's Courses

Founder of datalab.cc, author for LinkedIn Learning, associate professor of psychology at Utah Valley University. I teach people how to use data to find practical solutions to real-life problems. #DataIsForDoing

Linkedin Learning

View courses Linkedin Learning

LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.