Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Home

Lecture

Machine Learning Basics

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (39)

Untitled Log in to Mediaspace to watch this video

Supervised Learning Fundamentals Log in to Mediaspace to watch this video

Introduces the fundamentals of supervised learning, including loss functions and probability distributions.

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.

Regression: High Dimensions Log in to Mediaspace to watch this video

Explores linear regression in high dimensions and practical house price prediction from a dataset.

Linear Models: Part 1 Log in to Mediaspace to watch this video

Covers linear models, including regression, derivatives, gradients, hyperplanes, and classification transition, with a focus on minimizing risk and evaluation metrics.

Overfitting in Supervised Learning: Case Studies and Techniques Log in to Mediaspace to watch this video

Addresses overfitting in supervised learning through polynomial regression case studies and model selection techniques.

Linear Regression: Basics and Applications Log in to Mediaspace to watch this video

Covers the basics of linear regression in machine learning, exploring its applications in predicting outcomes like birth weight and analyzing relationships between variables.

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.

Linear Regression: Basics Log in to Mediaspace to watch this video

Covers the basics of linear regression, binary and multi-class classification, and evaluation metrics.

Machine Learning Review Log in to Mediaspace to watch this video

Covers a review of machine learning concepts, including supervised learning, classification vs regression, linear models, kernel functions, support vector machines, dimensionality reduction, deep generative models, and cross-validation.

Unsupervised Learning: Clustering & Dimensionality Reduction Log in to Mediaspace to watch this video

Introduces unsupervised learning through clustering with K-means and dimensionality reduction using PCA, along with practical examples.

Linear Regression and Logistic Regression Log in to Mediaspace to watch this video

Covers linear and logistic regression for regression and classification tasks, focusing on loss functions and model training.

Multilevel Models: Part 2 Log in to Mediaspace to watch this video

Explores advanced techniques in multilevel modeling, including fitting separate models, estimating coefficients, and checking residuals for model evaluation.

Least Squares Method Applications II Log in to Mediaspace to watch this video

Explores data approximation with non-linear curves using the least squares method in 2D and 3D spaces.

Learning in Artificial Neural Networks Log in to Mediaspace to watch this video

Discusses the evolution of artificial neural networks, challenges in supervised learning, and the role of innate behaviors in shaping behavior.

Transformers in Visual Intelligence Log in to Mediaspace to watch this video

Explores transformers in visual intelligence, focusing on object detection, image synthesis, and feature fusion.

Convolutional Networks: Motivation & Ideas Log in to Mediaspace to watch this video

Explores the motivation and ideas behind convolutional networks, emphasizing weight sharing and pooling layers.

Introduction to Financial Markets and Time Series Log in to Mediaspace to watch this video

Introduces financial markets, time series, machine learning applications in finance, and natural language processing.

Untitled Log in to Mediaspace to watch this video

Page 2 of 2