Factor Analysis Courses and Certifications

Fundamentals of Generative AI and Large Language Models: Theory and Practice

Explore the theory and practice of Generative AI, covering VAEs, GANs, Diffusion Models, Transformers, and LLMs with mathematical foundations and hands-on implementation skills.

• Swayam
• Self-Paced
• Free Online Course

Personality and psychological growth

Explore personality psychology's core theories, from psychoanalysis to behaviorism, while understanding human uniqueness, psychological growth, and the interplay between genetics and life experiences.

• XuetangX
• Self-Paced
• Free Online Course

IIT Roorkee;  NPTEL

Handling Large-Scale Unit Level Data

Learn to handle and analyze large-scale unit-level data using STATA. Covers data collection, tabulation, descriptive and inferential statistics, qualitative variables, and longitudinal data analysis for various fields.

• Swayam
• 8 weeks
• Self-Paced
• Free Online Course

Alexander Amini;  MIT

Deep Generative Modeling

1 rating

Explore deep generative modeling, including autoencoders, variational autoencoders, and GANs. Learn about latent variable models, reparameterization tricks, and recent advances in generative AI techniques.

• YouTube
• 1 hour 2 minutes
• Self-Paced
• Free Video

Alexander Amini;  MIT

Deep Generative Modeling

Explore deep generative modeling, including autoencoders, variational autoencoders, and GANs. Learn about latent variable models, reparameterization tricks, and recent advances in generative AI.

• YouTube
• 41 minutes
• Self-Paced
• Free Video

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
• Self-Paced
• Free Video

Can Diffusion Model Disentangle? A Theoretical Perspective

Explore a theoretical framework for understanding how diffusion models learn disentangled representations, with identifiability conditions, training dynamics analysis, and experimental validation across diverse tasks and modalities.

• YouTube
• 22 minutes
• Self-Paced
• Free Video

Yannic Kilcher

Topographic VAEs Learn Equivariant Capsules - Machine Learning Research Paper Explained

Explore Topographic VAEs: a novel approach to deep generative models with organized latent variables, bridging topographic organization and equivariance in neural networks for improved feature learning and transformation handling.

• YouTube
• 32 minutes
• Self-Paced
• Free Video

Yannic Kilcher

Self-Supervised Learning - The Dark Matter of Intelligence

Explore self-supervised learning as a promising approach for AI to develop background knowledge and common sense, with insights from Yann LeCun and Ishan Misra of Facebook AI Research.

• YouTube
• 59 minutes
• Self-Paced
• Free Video

Alexander Amini;  MIT

Deep Generative Modeling

Explore deep generative modeling, including autoencoders, VAEs, and GANs. Learn about latent variables, representation learning, and applications in debiasing and image synthesis.

• YouTube
• 55 minutes
• Self-Paced
• Free Video

Alexander Amini;  MIT

Deep Generative Modeling

Explore deep generative modeling, including autoencoders, VAEs, and GANs. Learn about latent variables, representation learning, and applications in image generation and domain transformation.

• YouTube
• 44 minutes
• Self-Paced
• Free Video

Alfredo Canziani

Energy Based Models and Self-Supervised Learning

Explore energy-based models, latent variables, and self-supervised learning. Dive into EBM training, inference, and comparison with probabilistic models. Discover contrastive methods and applications like K-means and BERT.

• YouTube
• 1 hour 37 minutes
• Self-Paced
• Free Video

Artem Kirsanov

Hidden Beauty Behind Generative AI: Variational Inference and ELBO

Delve into the mathematical foundations of generative AI through variational inference and ELBO concepts, exploring how intelligent systems model probability distributions effectively.

• YouTube
• 32 minutes
• Self-Paced
• Free Video

Alfredo Canziani

NYU Deep Learning - Fall 2022

Master neural network inference, energy-based classification, and latent variable models through PyTorch implementations and backpropagation techniques.

• YouTube
• 8 hours 30 minutes
• Self-Paced
• Free Video

Chemometrics & Machine Learning in Copenhagen

Basic Definition of Multivariate Data Analysis - Chemometrics

1 rating

Explore fundamental concepts of multivariate data analysis and chemometrics, including univariate vs. multivariate data, latent variables, and their applications in analytical chemistry.

• YouTube
• 26 minutes
• Self-Paced
• Free Video