Data Visualization: Principles and Practices

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (31)

PCA: Directions of Largest Variance

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

General Introduction to Data Science

Offers a comprehensive introduction to Data Science, covering Python, Numpy, Pandas, Matplotlib, and Scikit-learn, with a focus on practical exercises and collaborative work.

Unsupervised Learning: Dimensionality Reduction and Clustering

Covers unsupervised learning, focusing on dimensionality reduction and clustering, explaining how it helps find patterns in data without labels.

Dimensionality Reduction: PCA and LDA

Covers dimensionality reduction techniques like PCA and LDA, clustering methods, density estimation, and data representation.

Principal Component Analysis: Olympic Medals & Image Compression

Explores PCA for predicting medals distribution and compressing face images.

Data Preparation for Machine Learning: Categorical and Numerical Data

Explores data preparation for machine learning, emphasizing categorical to numerical conversion and effective data visualization techniques.

Data Visualization: Techniques, Tools & Concepts

Covers data visualization techniques, tools, and concepts for effective data representation.

Data Science Essentials

Covers the essentials of data science, including data handling, visualization, and analysis, emphasizing practical skills and active engagement.

Data Visualization: Techniques and Applications

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

Super-vision: Celebrating EPFL's Doctoral Theses History

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

Textual Data Analysis: Classification & Dimensionality Reduction

Explores textual data classification, focusing on methods like Naive Bayes and dimensionality reduction techniques like Principal Component Analysis.

Page 2 of 2