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Related lectures (32)

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Covers Gaussian Naive Bayes, K-nearest neighbors, and hyperparameter tuning in machine learning.

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Machine Learning: Supervised and Unsupervised Learning Techniques

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Provides an overview of the Apache Spark ecosystem, covering basics, operations, and key components.

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Overfitting in Supervised Learning: Case Studies and Techniques

Addresses overfitting in supervised learning through polynomial regression case studies and model selection techniques.

Recovering dynamical properties: Path Integral Methods

Explores deconvolution of GLE spectra to predict and extract dynamical properties from MD.

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Explores the transformative potential of IoT in workplaces and businesses, showcasing economic benefits, popular technologies, and vertical companies.

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Covers data stream processing with Apache Kafka and Spark, including event time vs processing time, stream processing operations, and stream-stream joins.

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