Dimensionality Reduction Courses and Certifications

Dimensionality Reduction in R

Learn dimensionality reduction techniques in R and master feature selection and extraction for your own data and models.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

Microcredential

Mastering Dimensionality Reduction with Python

8 ratings at CodeSignal

Master Python-based dimensionality reduction techniques from PCA to autoencoders, learning to extract essential features from complex datasets and optimize machine learning model performance through hands-on practice.

• CodeSignal
• 15 hours
• On-Demand
• Free Certificate
• 5 courses

Microcredential

Mastering Dimensionality Reduction with R

Discover how to simplify complex data using PCA, linear/non-linear techniques, autoencoders, and feature selection in R for enhanced machine learning performance.

• CodeSignal
• 15 hours
• On-Demand
• Free Certificate
• 5 courses

Non-linear Dimensionality Reduction Techniques

Master t-SNE, LLE, and Kernel PCA techniques to reveal hidden patterns and reduce dimensionality in complex, high-dimensional datasets using R programming.

• CodeSignal
• 3 hours
• On-Demand
• Free Certificate

Non-linear Dimensionality Reduction Techniques

1 review

Master non-linear dimensionality reduction techniques like t-SNE, LLE, and Kernel PCA to uncover hidden patterns in complex datasets through hands-on visualization and parameter tuning.

• CodeSignal
• 3 hours
• On-Demand
• Free Certificate

MITCBMM

Dimensionality Reduction for Matrix- and Tensor-Coded Data

Explore matrix and tensor factorizations for data compression, including PCA, NMF, and CP tensor decomposition. Learn theoretical foundations and practical applications in scientific domains.

• YouTube
• 54 minutes
• On-Demand
• Free Video

Simons Institute

Sketching for Linear Algebra - Basics of Dimensionality Reduction and CountSketch II

Explore dimensionality reduction and CountSketch techniques in linear algebra, focusing on advanced applications and theoretical foundations for data science.

• YouTube
• 1 hour 10 minutes
• On-Demand
• Free Video

Simons Institute

Sketching for Linear Algebra - Basics of Dimensionality Reduction and CountSketch I

Explore dimensionality reduction and CountSketch techniques for efficient linear algebra computations, focusing on regression analysis and subspace embeddings.

• YouTube
• 59 minutes
• On-Demand
• Free Video

MITCBMM

Dimensionality Reduction for Matrix- and Tensor-Coded Data

Explore advanced dimensionality reduction techniques for matrix and tensor data, focusing on CP tensor decomposition. Learn theoretical foundations and practical applications in neuroscience.

• YouTube
• 46 minutes
• On-Demand
• Free Video

Applied Algebraic Topology Network

Dimensionality Reduction via Distributed Persistence - DIPOLE

Explore dimensionality reduction with DIPOLE, a novel approach combining local metric and global topological preservation for improved data visualization and analysis.

• YouTube
• 59 minutes
• On-Demand
• Free Video

MITCBMM

Dimensionality Reduction II

Explore advanced dimensionality reduction techniques, including PCA and negentropy, with practical applications in brain and cognitive sciences. Includes exercises and research discussions.

• YouTube
• 30 minutes
• On-Demand
• Free Video

UofU Data Science

Dimensionality Reduction: Rank-k Approximation and Eigen-decomposition - Lecture 20

Dive into advanced dimensionality reduction techniques, exploring rank-k approximation, eigen-decomposition, and power method applications in data analysis.

• YouTube
• 1 hour 21 minutes
• On-Demand
• Free Video

UofU Data Science

Dimensionality Reduction: Data Matrices and Projection Methods - Lecture 18

Explore dimensionality reduction techniques through matrix operations, focusing on dot product projections and orthogonal basis sets for effective data transformation.

• YouTube
• 51 minutes
• On-Demand
• Free Video

DigitalSreeni

Advanced Dimensionality Reduction - t-SNE vs UMAP vs PCA Deep Dive

Master non-linear dimensionality reduction with t-SNE and UMAP for complex data visualization, including parameter tuning and Python implementation using breast cancer classification.

• YouTube
• 30 minutes
• On-Demand
• Free Video

Dimensionality Reduction in Python

13 ratings at DataCamp

Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available