Click the Launch Binder tab below tolaunch a live instance of the Jupyter notebooks in this repo.
This repo contains an iteractive demo of face detection using a linear Support Vector Machine classifier, an algorithm introduced in the introductory lectures for Udacity's Machine Learning Nanodegree program. This interactive demo comes in the form of Python based Jupyter notebooks (these are files with the extension .ipynb), which is a convenient open source platform for using Python to perform machine learning (and more generally computational science) tasks.
A short description of the notebooks in this repo include:
face_detection_demo.ipynb - this introduces the concept of "face detection" a.k.a. how to automatically find (human) faces in digital images. This machine learning task is used to e.g., organize photos (as Facebook does with tags), tell your smartphone where to focus when taking a picture (on the faces, as opposed to the background), or make augmented reality based selfies (as Snapchat does with lenses). In this demo you will have the chance to train your own Support Vector Machine classifier on a small dataset of images to perform this task.
To see a rubric for this project (a high level overview of what we hope you gain from using these notebooks) see MLND_lab_face_detection_rubric.pdf, located in this repo.