Linear Discriminant Analysis Courses and Certifications

Linear Landscapes of Dimensionality Reduction

Master dimensionality reduction techniques through Linear Discriminant Analysis (LDA), comparing it with PCA while implementing practical Python solutions for improved feature selection and model performance.

• CodeSignal
• On-Demand
• Free Certificate

NPTEL-NOC IITM

Implementing Linear Discriminant Analysis (LDA) with Irish Data Sets in R

Implement LDA using Irish datasets in R, gaining practical experience with Linear Discriminant Analysis techniques.

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

Microcredential

Mastering Dimensionality Reduction with Python

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
• On-Demand
• Free Certificate
• 5 courses

Logistic Regression in Python

899 ratings at Udemy

Logistic regression in Python tutorial for beginners. You can do Predictive modeling using Python after this course.

• Udemy
• 7 hours 39 minutes
• On-Demand
• Paid Course

Logistic Regression in R Studio

387 ratings at Udemy

Logistic regression in R Studio tutorial for beginners. You can do Predictive modeling using R Studio after this course.

• Udemy
• 6 hours 17 minutes
• On-Demand
• Paid Course

Machine Learning

1 review

Comprehensive introduction to machine learning concepts, from fundamentals to advanced techniques, with clear explanations and practical applications.

• YouTube
• 22 hours
• On-Demand
• Free Video

Face Recognition Techniques and Applications - Lecture 14

Explore face recognition techniques, from simple approaches to advanced methods like PCA and Linear Discriminant Analysis. Learn about eigenvectors, image compression, and scatter matrices.

• YouTube
• 1 hour 11 minutes
• On-Demand
• Free Video

Reducing Dimensions in Data with scikit-learn

19 ratings at Pluralsight

Learn powerful dimensionality reduction techniques in scikit-learn to optimize ML models, reduce overfitting, speed up training, and improve visualization. Covers feature selection, PCA, LDA, and manifold learning methods.

• Pluralsight
• 2-3 hours
• On-Demand
• Free Trial Available

UofU Data Science

Linear Classification and Loss Functions - Lecture 25

Dive into linear classifiers and loss functions, mastering fundamental concepts for effective data classification and model optimization techniques.

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

UofU Data Science

Multidimensional Scaling and Linear Discriminant Analysis in Data Mining - Spring 2023

Explore multidimensional scaling (MDS) and linear discriminant analysis (LDA), learning key concepts, motivations, and practical applications in data dimensionality reduction and classification.

• YouTube
• 1 hour 11 minutes
• On-Demand
• Free Video

NPTEL-NOC IITM

Multi-Class Classification with Discriminant Analysis

Learn discriminant analysis techniques for multi-class classification, covering data collection, distributions, decision boundaries, and linear approaches to effectively categorize new data points.

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

Applying the Mathematical MASS Model with R

This course focuses on capabilities, models, and datasets available within the MASS package in R. Along the way, you will gain knowledge of estimating survival probabilities and working with hazard rates in multi-state model.

• Pluralsight
• 2-3 hours
• On-Demand
• Free Trial Available

Performing Dimension Analysis with R

This course covers virtually all of the important techniques of dimensionality reduction available in R, allowing model builders to optimize model performance by reducing overfitting and saving on model training time and cost.

• Pluralsight
• 2-3 hours
• On-Demand
• Free Trial Available

statisticsmatt

Multivariate

Explore advanced multivariate statistical concepts, including hypothesis testing, probability distributions, and data analysis techniques, with practical applications using R programming.

• YouTube
• 6 hours
• On-Demand
• Free Video

Great Learning

Linear Discriminant Analysis - Discriminant Analysis Tutorial - Machine Learning Tutorial

Explore Linear Discriminant Analysis for dimension reduction and pattern classification in machine learning. Learn its applications, core mathematics, and practical implementation through exercises and examples.

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