Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Practice
Publications
Startups
Units
Show all results for
Home
Lecture
Machine Learning: Inferring Information From Data
Graph Chatbot
Related lectures (32)
Previous
Page 1 of 4
Next
Machine Learning at the Atomic Scale
Explores simple models, electronic structure evaluation, and machine learning at the atomic scale.
Regression Trees and Ensemble Methods in Machine Learning
Discusses regression trees, ensemble methods, and their applications in predicting used car prices and stock returns.
Machine Learning: Supervised and Unsupervised Learning Techniques
Covers supervised and unsupervised learning techniques in machine learning, highlighting their applications in finance and environmental analysis.
Machine Learning Biases
Covers the basics of machine learning, challenges in deployment, adversarial attacks, and privacy concerns.
Supervised Learning Overview
Covers CNNs, RNNs, SVMs, and supervised learning methods, emphasizing the importance of tuning regularization and making informed decisions in machine learning.
Supervised Learning: Classification Algorithms
Explores supervised learning in financial econometrics, emphasizing classification algorithms like Naive Bayes and Logistic Regression.
Statistical Learning: Fundamentals
Introduces the fundamentals of statistical learning, covering supervised learning, decision theory, risk minimization, and overfitting.
Introduction to Machine Learning
Covers the basics of machine learning, including supervised and unsupervised learning, linear regression, and classification.
Fundamentals of Inference and Learning
Covers the theory of statistics, inference, and machine learning with practical exercises in Python.
Introduction to Machine Learning
Provides an overview of Machine Learning, including historical context, key tasks, and real-world applications.