Vehicle Detection and Tracking using Machine Learning and HOG

I am into my first term of Udacity's Self Driving Car Nanodegree and I want to share my experience regarding the final project of Term 1 i.e. The complete code can be found here. The basic objective of this project is to apply the concepts of HOG and Machine Learning to detect a Vehicle from a dashboard video. Sure, the Deep Learning implementations like YOLO and SSD that utilize convolutional neural network stand out for this purpose but when you are a beginner in this field, its better to start with the classical approach. The most important thing for any machine learning problem is the labelled data set and here we need to have two sets of data: Vehicle and Non Vehicle Images.