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Explores smart, connected products and their transformative impact on companies, covering artificial intelligence, machine learning, predictive models, forecasting methods, and more.
Introduces the fundamentals of regression in machine learning, covering course logistics, key concepts, and the importance of loss functions in model evaluation.
Explores the evolution of cloud computing to support IoT applications and the challenges faced by deep learning algorithms in processing data from smart sensors.
Delves into the intersection of physics and data in machine learning models, covering topics like atomic cluster expansion force fields and unsupervised learning.
Introduces the Applied Data Analysis course at EPFL, covering a broad range of data analysis topics and emphasizing continuous learning in data science.
