Lecture

Machine Learning Biases

Related lectures (122)
Machine Learning at the Atomic Scale
Explores simple models, electronic structure evaluation, and machine learning at the atomic scale.
Binary Classification by Regression: Decision Functions and Cost Functions
Explores binary classification by regression, decision functions, and various cost functions.
Decision Trees: Induction & Attributes
Explores decision trees, attribute selection, bias-variance tradeoff, and ensemble methods in machine learning.
Perception: Image Classification Challenges
Covers image classification challenges, machine learning concepts, linear regression, and nearest neighbor approach in autonomous vehicles.
Introduction to Machine Learning
Introduces machine learning concepts, from basics to advanced neural networks.
Machine Learning Applications: Regression and Classification
Explores machine learning applications in materials modeling, covering regression, classification, and feature selection.
Machine Learning for Plant Identification
Delves into challenges of supervised learning in citizen science, focusing on plant species recognition and label aggregation.
Introduction to Machine Learning
Introduces fundamental machine learning concepts and algorithms for model training and evaluation.
Smart, Connected Products
Explores smart, connected products and their transformative impact on companies, covering artificial intelligence, machine learning, predictive models, forecasting methods, and more.
Theory of Computation: Monotone Complexity and XOR-SAT Lower Bounds
Explores monotone complexity, XOR-SAT lower bounds, and their implications in computational theory.

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.