Dimensionality Reduction Courses and Certifications

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Dimensional Reduction Using PaCMAP: From High-Dimensional Data to Vector Spaces - MNIST Case Study

Explore dimensional reduction using PaCMAP algorithm, from basic implementation to advanced applications with MNIST datasets, featuring hands-on Python coding in Colab notebooks.

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

CIMPA UCR

Multidimensional Scaling by Particle Swarm Optimization

Explora el escalamiento multidimensional mediante optimización por enjambre de partículas con el experto Javier Trejos.

• YouTube
• 1 hour 27 minutes
• On-Demand
• Free Video

Big Data Analytics in Healthcare

In this course, we introduce the characteristics of medical data and associated data mining challenges on dealing with such data. We cover various algorithms and systems.

• Udacity
• 8 weeks
• On-Demand
• Free Online Course

Deep Generative Models - Lecture 5: Variational Autoencoders

Explore Variational Autoencoders (VAEs) in deep generative modeling, covering theoretical foundations and practical applications in this comprehensive Stanford lecture.

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

Deep Generative Models - Lecture 6: Variational Autoencoders

Explore Variational Autoencoders (VAEs) in deep generative modeling, covering theoretical foundations and practical applications in this Stanford lecture by Prof. Stefano Ermon.

• YouTube
• 1 hour 22 minutes
• On-Demand
• Free Video

Navigating Data Simplification with PCA

Master dimensionality reduction techniques using Principal Component Analysis (PCA) with Python's Scikit-learn, from basic concepts to practical implementation in machine learning projects.

• CodeSignal
• On-Demand
• Free Certificate

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

Enigmatic Autoencoders for Dimensionality Reduction

Dive into the world of autoencoders, mastering neural network architecture, forward propagation, and hyperparameter optimization for effective data compression and reconstruction techniques.

• CodeSignal
• On-Demand
• Free Certificate

Dimensionality Reduction with Feature Selection

Master advanced feature selection techniques to optimize machine learning models through variance analysis, univariate selection, mutual information, and recursive elimination methods.

• CodeSignal
• On-Demand
• Free Certificate

Intro to Unsupervised Machine Learning

Master unsupervised machine learning through hands-on practice with clustering, dimensionality reduction, and advanced algorithms using the Iris dataset for practical data analysis applications.

• CodeSignal
• On-Demand
• Free Certificate

Unsupervised Learning and Clustering

Master unsupervised learning algorithms from scratch, including k-Means, PCA, and DBSCAN. Build clustering implementations, visualize results, and evaluate performance using essential metrics.

• CodeSignal
• On-Demand
• Free Certificate

Feature Engineering for Text Classification

Master text classification techniques through hands-on practice with tokenization, Bag-of-Words, TF-IDF, sparse matrices, and dimensionality reduction for effective natural language processing applications.

• CodeSignal
• On-Demand
• Free Certificate

Materials Data Sciences and Informatics

341 ratings at Coursera

Explore materials informatics at the intersection of materials science, computational science, and information science. Learn data-driven approaches to accelerate materials development and deployment.

• Coursera
• 9 hours 10 minutes
• On-Demand
• Free Online Course (Audit)

Mathematics for Machine Learning: PCA

3098 ratings at Coursera

Explore mathematical foundations of Principal Component Analysis (PCA) for dimensionality reduction. Learn statistics, inner products, orthogonal projections, and derive PCA from a geometric perspective.

• Coursera
• 20 hours 39 minutes
• On-Demand
• Free Online Course (Audit)

Data Visualization for Genome Biology

20 ratings at Coursera

Explore genome biology data visualization through hands-on labs using web tools and R. Learn theoretical concepts, practical techniques, and best practices for creating informative biological data plots.

• Coursera
• 15 hours 20 minutes
• On-Demand
• Free Online Course (Audit)