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Explores the structured approach to exploratory spatial data analysis, emphasizing the importance of analytical frameworks and the Visual Seeking Mantra.
Introduces the Applied Data Analysis course at EPFL, covering a broad range of data analysis topics and emphasizing continuous learning in data science.
Explores mapping non-linear data to higher dimensions using SVM and covers polynomial feature expansion, regularization, noise implications, and curve-fitting methods.
Covers data stream processing concepts, focusing on Apache Kafka and Spark Streaming integration, event time management, and project implementation guidelines.
Introduces exploratory data analysis in environmental health, covering its definition, techniques, and applications in georeferenced health data analysis.