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
Introduction to Supervised Learning and Decision Theory
Graph Chatbot
Related lectures (51)
Supervised Learning Fundamentals
Log in to Mediaspace to watch this video
Introduces the fundamentals of supervised learning, including loss functions and probability distributions.
Binary Classification by Regression: Decision Functions and Cost Functions
Log in to Mediaspace to watch this video
Explores binary classification by regression, decision functions, and various cost functions.
Optimality in Decision Theory: Unbiased Estimation
Log in to Mediaspace to watch this video
Explores optimality in decision theory and unbiased estimation, emphasizing sufficiency, completeness, and lower bounds for risk.
Parametric Regressions: Linear Regression
Log in to Mediaspace to watch this video
Explores parametric regressions, emphasizing linear regression's simplicity and complexity trade-offs between parametric and non-parametric models.
Machine Learning Basics
Log in to Mediaspace to watch this video
Covers the basics of machine learning, including supervised and unsupervised techniques, linear regression, and model training.
Statistical Theory: Decision Theory Framework
Log in to Mediaspace to watch this video
Explores the Decision Theory Framework in Statistical Theory, viewing statistics as a random game with key concepts like admissibility, minimax rules, and Bayes rules.
Decisions under Risk and Uncertainty: Behavioral Economics Insights
Log in to Mediaspace to watch this video
Delves into decision-making under risk, bounded rationality, prospect theory, and framing, with insights from behavioral economics.
Image Classification: Decision Trees & Random Forests
Log in to Mediaspace to watch this video
Explores image classification using decision trees and random forests to reduce variance and improve model robustness.
Linear Regression: Basics and Gradient Descent
Log in to Mediaspace to watch this video
Covers the basics of linear regression, including feature engineering, supervised vs. unsupervised learning, and minimizing the cost function.
Untitled
Log in to Mediaspace to watch this video
Introduction to Image Classification
Log in to Mediaspace to watch this video
Covers image classification, clustering, and machine learning techniques like dimensionality reduction and reinforcement learning.
Optimization of Paper Planes
Log in to Mediaspace to watch this video
Explores the optimization of paper planes and soft structures for thrust generation.
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.
Optimal Errors and Phase Transitions
Log in to Mediaspace to watch this video
Explores optimal errors and phase transitions in high dimensional models.
Concept Selection and Tradespace Exploration
Log in to Mediaspace to watch this video
Covers decision analysis, concept selection methods, non-dominance, and optimization in system design.
Machine Learning: Supervised and Unsupervised Learning Techniques
Log in to Mediaspace to watch this video
Covers supervised and unsupervised learning techniques in machine learning, highlighting their applications in finance and environmental analysis.
Information Extraction: Approaches and Techniques
Log in to Mediaspace to watch this video
Covers Information Extraction approaches, including hand-written patterns and supervised learning.
Model Evaluation
Log in to Mediaspace to watch this video
Explores underfitting, overfitting, hyperparameters, bias-variance trade-off, and model evaluation in machine learning.
Improving Models of the Ventral Visual Pathway
Log in to Mediaspace to watch this video
Explores computational models of the ventral visual system, focusing on optimizing networks for real-world tasks and comparing to brain data.
Advanced Information Theory: F-Divergences and Generalization Error
Log in to Mediaspace to watch this video
Covers f-divergences and generalization error in advanced information theory.
Previous
Page 2 of 3
Next
