Professional Certificate in PCA Applications: Real-World Scenarios
-- ViewingNowThe Professional Certificate in PCA (Principal Component Analysis) Applications: Real-World Scenarios is a crucial course that provides learners with essential skills for data analysis and machine learning. PCA is a powerful statistical technique used to analyze large datasets and extract key information, making it invaluable in fields such as finance, engineering, and healthcare.
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โข Principles of PCA: Introduction to Principal Component Analysis, Linear Algebra Refresher, Singular Value Decomposition
โข Data Preprocessing: Data Cleaning, Normalization, Outlier Detection and Removal
โข Implementing PCA: Choosing the Number of Components, Mean Normalization, Covariance and Correlation Matrices
โข PCA in Real-World Scenarios: Image Compression, Face Recognition, Text Analysis, Genomics Data Analysis
โข PCA Variations: Kernel PCA, Probabilistic PCA, Non-negative Matrix Factorization
โข Evaluating PCA: Reconstruction Error, Explained Variance, Scree Plot
โข PCA Limitations: Curse of Dimensionality, Loss of Interpretability, Assumptions and Limitations
โข PCA Alternatives: t-SNE, Autoencoders, Multidimensional Scaling
โข Research Topics in PCA: Deep Learning-based PCA, Online PCA, Incremental PCA
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