Big Data Projects (2024 Level II CFA® Exam –Quantitative Methods–Module 7)

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Topic 1 – Quantitative Methods
Module 7 – Machine Learning
0:00 LOS: Introduction and Learning Outcome Statements
7:25 LOS: Distinguish between supervised machine learning, unsupervised machine learning, and deep learning;
15:40 LOS: Describe over fitting and identify methods of addressing it;
20:54 LOS: Describe supervised machine learning algorithms—including penalized regression, support vector machine, k-nearest neighbor, classification and regression tree, ensemble learning, and random forest—and determine the problems for which they are best suited;
46:17 LOS: Describe unsupervised machine learning algorithms—including principal components analysis, K-means clustering, and hierarchical clustering—and determine problems for which they are best suited;
56:09 LOS: Describe neural networks, deep learning nets, and reinforcement learning.

[mosw]

characteristics of big data are 4 v's not 3 ( volume, variety, velocity & "veracity")