Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Quizes
Exercises
Publications
Startups
Units
Show all results for
Home
Lecture
Prevalence Surveys for Neglected Tropical Diseases
Graph Chatbot
Related lectures (52)
Statistical Analysis of Networks: Link Prediction and Biclustering
Log in to Mediaspace to watch this video
Explores link prediction, logistic regression, causal inference, and biclustering in statistical network analysis.
Regression Trees and Ensemble Methods in Machine Learning
Log in to Mediaspace to watch this video
Discusses regression trees, ensemble methods, and their applications in predicting used car prices and stock returns.
Supervised Learning Fundamentals
Log in to Mediaspace to watch this video
Introduces the fundamentals of supervised learning, including loss functions and probability distributions.
Binary Response: Link Functions
Log in to Mediaspace to watch this video
Explores binary response interpretation, link functions, logistic regression, and model selection using deviances and information criteria.
Machine Learning Fundamentals: Regularization and Cross-validation
Log in to Mediaspace to watch this video
Explores overfitting, regularization, and cross-validation in machine learning, emphasizing the importance of feature expansion and kernel methods.
Efficient Machine Learning via Data Summarization
Log in to Mediaspace to watch this video
Explores efficient machine learning through data summarization, covering challenges, methods, and impactful applications in various domains.
Document Analysis: Topic Modeling
Log in to Mediaspace to watch this video
Explores document analysis, topic modeling, and generative models for data generation in machine learning.
Marginal Models: Interpretation and Application
Log in to Mediaspace to watch this video
Explores marginal models in modern regression, emphasizing interpretation and application in statistical analysis.
Linear and Logistic Regression
Log in to Mediaspace to watch this video
Introduces linear and logistic regression, covering parametric models, multi-output prediction, non-linearity, gradient descent, and classification applications.
Logistic Regression: Classification
Log in to Mediaspace to watch this video
Covers supervised learning, classification using logistic regression, and challenges in optimization.
Linear Models: Part 2
Log in to Mediaspace to watch this video
Covers linear models, binary and multi-class classification, and logistic regression with practical examples.
Linear Models: Continued
Log in to Mediaspace to watch this video
Explores linear models, regression, multi-output prediction, classification, non-linearity, and gradient-based optimization.
Linear Models & k-NN
Log in to Mediaspace to watch this video
Covers linear models, logistic regression, decision boundaries, k-NN, and practical applications in authorship attribution and image data analysis.
Supervised Learning: Classification Algorithms
Log in to Mediaspace to watch this video
Explores supervised learning in financial econometrics, emphasizing classification algorithms like Naive Bayes and Logistic Regression.
Polynomial Regression: Overview
Log in to Mediaspace to watch this video
Covers polynomial regression, flexibility impact, and underfitting vs overfitting.
Latent Space Models: Inference and Applications
Log in to Mediaspace to watch this video
Explores latent space models, network representations, spectral decompositions, and parameter estimation methods.
Generalized Linear Models
Log in to Mediaspace to watch this video
Covers Generalized Linear Models, likelihood, deviance, link functions, sampling methods, Poisson regression, over-dispersion, and alternative regression models.
Data-Driven Modeling: Regression
Log in to Mediaspace to watch this video
Introduces data-driven modeling with a focus on regression, covering linear regression, risks of inductive reasoning, PCA, and ridge regression.
Linear Regression: Basics and Estimation
Log in to Mediaspace to watch this video
Covers the basics of linear regression and how to solve estimation problems using least squares and matrix notation.
Feature Engineering: Polynomial Regression
Log in to Mediaspace to watch this video
Covers fitting linear regression on features of the original predictors for flexible feature representation.
Previous
Page 2 of 3
Next
