The primary goal of this project was to build an accurate and reliable car image detection model. We fitted various conventional models after some mandatory data preprocessing of the image dataset. By employing a dimensionality reduction technique, we were able to reduce the time and complexity of models and ultimately improve their performance.

We also implemented Deep Learning Techniques like Feed Forward Neural Networks and Recurrent Neural Networks to improve the accuracy even more.

This file contains the code for Deep Learning algorithms that are used for image classification. It is implemented in Python using Tensorflow.

This file contains the supervised machine learning algorithms that were used to classify images. It is implemented in R.

This file contains the summary of analysis in the form of a report.