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Related lectures (32)

Page 2 of 4

Delves into data physicalization, expressiveness, feminist visualization, and the balance between exploration and explanation in data visualization.

Data Science Essentials: Pandas, Numpy, Matplotlib

Introduces Pandas, Numpy, and Matplotlib for data analysis and visualization in Python.

Introduction to Machine Learning: Course Overview and Basics

Introduces the course structure and fundamental concepts of machine learning, including supervised learning and linear regression.

Data Science for Engineers: Part 2

Explores data manipulation, exploration, and visualization in data science projects using Python.

Data Visualization: Principles and Practices

Explores data visualization principles, including chart navigation, histograms, scatter plots, box plots, and color usage.

Data Analysis: KMnO4 Concentrations

Covers the analysis of KMnO4 concentrations using data from a CSV file.

Data Science Fundamentals

Covers the fundamentals of data science, emphasizing breadth over depth and practical application in machine learning and data analysis.

Regulations: Figures of Regulations

Covers the analysis of ECG heart rate data and respiratory flow measurements using Excel.

Digital History and Digitized Press

Delves into the 'digital turn' in history, examining historical research using digitized newspapers and exploring text reuse, word embeddings, and data visualization.

Digital Urban History: QGIS Practical Session

Covers the practical use of QGIS for spatial data analysis and visualization, including georeferencing historical maps and manipulating vector data.