Introduction: Applied Machine Learning

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Related lectures (32)

Regression Trees and Ensemble Methods in Machine Learning

Discusses regression trees, ensemble methods, and their applications in predicting used car prices and stock returns.

Generalization Error

Explores generalization error in machine learning, focusing on data distribution and hypothesis impact.

Evaluating Machine Accuracy and Robustness on ImageNet

Explores the evaluation of machine and human accuracy and robustness on ImageNet, highlighting progress, challenges, and the need for improvement.

Artificial Intelligence: The New Radical Addition to Work

Explores the convergence of IoT, Big Data, and Deep Learning in Artificial Intelligence applications across various industries.

Machine Learning Fundamentals

Covers the fundamental principles and methods of machine learning, including supervised and unsupervised learning techniques.

Multimodal Analytics: Human-Robot Interaction and Learning Processes

Delves into Human-Robot Interaction, student engagement, and learning analytics using multimodal data to enhance educational processes.

Data Analysis to AI and ML, Social Media

Explores the evolution from data analysis to AI and ML, emphasizing big data, machine learning, and social media interaction.

Machine Learning at the Atomic Scale

Explores simple models, electronic structure evaluation, and machine learning at the atomic scale.

Machine Learning Fundamentals

Introduces the basics of machine learning, covering supervised classification, logistic regression, and maximizing the margin.

Introduction to Applied Data Analysis

Introduces the Applied Data Analysis course at EPFL, covering a broad range of data analysis topics and emphasizing continuous learning in data science.

Pitfalls and Caveats in Machine Learning

Covers challenges in machine learning, emphasizing the importance of choosing relevant data and algorithms.

Deep Learning: Data Representations and Neural Networks

Covers data representations, Bag of Words, histograms, data pre-processing, and neural networks.

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