
Learn hierarchical clustering using College Scorecard data to group similar schools. Explore clustering methods, data preparation, and practical application for student decision-making in higher education.

Discover a complete ML-based anomaly detection pipeline for microcontrollers, featuring real-time sensor value processing, automatic hyperparameter tuning, and high-speed inference capabilities.

Explore flat clustering with KMeans using Scikit-learn and Python. Learn to categorize unlabeled data into specified groups through hands-on coding and visualization techniques.

Explore unsupervised machine learning techniques for analyzing stellar spectra using deep normalizing flows, with applications in galaxy evolution and big data astronomy.

Explore advanced NLP techniques for enterprise search query expansion, leveraging unsupervised machine learning to analyze term relationships and improve complex technical content discovery.

Explore unsupervised ML algorithms for scalable data quality monitoring in Databricks, covering implementation, strengths, weaknesses, and practical applications for effective data management.

Einführung in Generative Adversarial Networks: Überblick, Geschichte und praktische Anwendungen für Entwickler. Erklärt Konzepte, Techniken und Herausforderungen anhand von Beispielen wie Pokémon-Generator und Gesichtsalterung.

Explore real-world applications of data science, from label data to unsupervised machine learning, with practical examples in wind energy, object detection, and automotive industries.

Explore Go's applications in aerospace, from orbital simulations to rocket engine testing. Learn how this language is revolutionizing space technology development in Argentina.

Demystifies AI and machine learning for SOC teams, focusing on practical applications like data leak prevention. Includes live demo and insights from Credit Agricole's SOC experience.