Understanding and Applying Factor Analysis and PCA
Understanding and Applying Factor Analysis and PCA
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 2.5 Hours | 324 MB
Genre: eLearning | Language: English
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 2.5 Hours | 324 MB
Genre: eLearning | Language: English
Factor Analysis and PCA are powerful tools, applicable in many common situations in business and data analysis. This course covers both the theory and implementation of factor analysis and PCA, in Excel (using VBA), Python, and R.
Factor Analysis and PCA are key techniques for dimensionality reduction, and latent factor identification. In this course, Understanding and Applying Factor Analysis and PCA, you'll learn how to understand and apply factor analysis and PCA. First, you'll explore how to cut through the clutter with factor analysis. Next, you'll discover how to carry out factor analysis using PCA, a powerful ML-based approach. Then, you'll learn how to perform eigenvalue decomposition, a cookie-cutter linear algebra procedure. Finally, you'll learn how to implement PCA to explain Google's stock returns in Excel and VBA, R, and Python. By the end of this course, you'll have a strong applied knowledge of factor analysis and PCA that will help you solve complex business problems.
Understanding and Applying Factor Analysis and PCA
