Refer Dataset- https://www.kaggle.com/hereisburak/pins-face-recognition

DOMAIN: Face recognition • CONTEXT: Company X intends to build a face identification model to recognise human faces. • DATA DESCRIPTION: The dataset comprises of images and its mask where there is a human face. • PROJECT OBJECTIVE: Face Aligned Face Dataset from Pinterest. This dataset contains 10,770 images for 100 people. All images are taken from 'Pinterest' and aligned using dlib library. Some data samples:

• TASK: In this problem, we use a pre-trained model trained on Face recognition to recognise similar faces. Here, we are particularly interested in recognising whether two given faces are of the same person or not. Below are the steps involved in the project. • Load the dataset and create the metadata. • Check some samples of metadata. • Load the pre-trained model and weights. • Generate Embedding vectors for each face in the dataset. • Build distance metrics for identifying the distance between two given images. • Use PCA for dimensionality reduction. • Build an SVM classifier in order to map each image to its right person. • Import the the test image. Display the image. Use the SVM trained model to predict the face.