Duration: 3h 51m | Video: .MP4 1280x720, 30 fps(r) | Audio: AAC, 48000 Hz, 2ch | Size: 775 MB
Genre: eLearning | Language: English
Data science continues to grow in sophistication and demand at an exponential rate.
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 that can only be spotted after disentangling seasonal and random effects, and new methods for predicting important outcomes. Instructor Barton Poulson focuses on data mining in R, presents a broad range of algorithms including machine learning methods, and offers important information on laws and policies that affect data mining. Barton gives an overview of dimensionality reduction. He introduces clustering, including hierarchical clustering, then goes into association analysis. He explains -series mining and decomposition, then concludes with text mining, sennt analysis, and sennt scoring.
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