Installation: GNU Octave 3.8.0

Related lectures (31)

Page 2 of 4

Discusses numerical methods, focusing on stopping criteria, SciPy for optimization, and data visualization with Matplotlib.

Covers PCA, finding directions of largest variance, data dimensionality reduction, and limitations of PCA.

Covers Principal Component Analysis for dimension reduction in biological data, focusing on visualization and pattern identification.

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

Discusses the bisection method for solving nonlinear equations and its implementation using Python with NumPy and Matplotlib.

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

Explores EPFL's doctoral theses history, data visualization, and the innovative D3 approach.

Introduces NumPy and Matplotlib, essential tools for scientific computing and data visualization in Python.

Explores data visualization techniques, design impact, and interactive applications for effective information communication.

Explores techniques and applications of data visualization, emphasizing the importance of effective communication and unconventional examples.