Graduate Certificate in Dimensionality Reduction in Feature Engineering
-- ViewingNowThe Graduate Certificate in Dimensionality Reduction in Feature Engineering is a comprehensive course that addresses the critical need for data professionals to master feature engineering and dimensionality reduction techniques. In an era of big data and AI, these skills are in high demand across industries, with companies seeking experts who can turn raw data into actionable insights.
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⢠Introduction to Dimensionality Reduction in Feature Engineering
⢠Linear Dimensionality Reduction Techniques: Principal Component Analysis (PCA)
⢠Advanced Linear Dimensionality Reduction: Linear Discriminant Analysis (LDA)
⢠Non-Linear Dimensionality Reduction: t-Distributed Stochastic Neighbor Embedding (t-SNE)
⢠Non-Linear Dimensionality Reduction: Autoencoders in Feature Engineering
⢠Feature Selection vs. Dimensionality Reduction
⢠Dimensionality Reduction for Text Data: Latent Dirichlet Allocation (LDA)
⢠Evaluation Metrics for Dimensionality Reduction Techniques
⢠Real-World Applications of Dimensionality Reduction in Feature Engineering
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