Instructor: Paul Li
Team Leads: Elias Saravia, Monica Wilkinson
Developers: Maria Sooklaris, Joshua Asuncion, Keilyn Yuzuki
This notebook provides an elementary introduction to how data science is used in the field of computer vision and cognitive science, including the benefits of risks of drawing conclusions from large data sets. This notebook uses the Database of Faces from AT&T Laboratories Cambridge, also available as the Olivetti Faces Dataset in sklearn. The main activity in this notebook focuses on the advantages and drawbacks of simplifying large data sets.
Sources and Contributions
| Author | Usage | Source |
|---|---|---|
| Gael Varoquaux | Adapted example for "Dimensionality Reduction" section. | Link |
| Jake VanderPlas | Adapted example for "Dimensionality Reduction" section. | Link |
| Jupyter Widgets | Adapted code for widget. | Link |
| Raluca Budiu | Adapted article for "Why Would We Simplify Data?" section. | Link |
| Scikit-learn | Used Olivetti Faces dataset. | Link |
| Viatcheslav Wlassoff | Adapted article for "How Do Humans Recognize Faces?" section. | Link |