In today's world, it has become customary to collect opinions and reviews from people through various surveys, polls, social media platform and analyse them in order to understand the preferences of customers. So, in order to understand the sentiments of customers and their view on the services offered by producers, there comes the need for an accurate and canonical mechanism for speculating and anticipating sentiments which possess the ability to fabricate a positive or negative impact in the market and thus making this kind of analysis important for the pair of producers and consumers. In this paper, the main focus is to anatomize the reviews conveyed by viewers on various movies and to use this analysis to understand the customers' sentiments and market behaviour for better customer experience.This paper intends to analyse the reviews of customers on various movies by implementing three algorithms namely K Nearest Neighbours, Logistic Regression and Naive Bayes and provides conclusive remarks.

It includes Deep Learning techniques using convolutional neural networks for getting the predictions and probabilities for the best decision that has to be made while driving a car like lane detection, traffic signals recognition and their localization and simultaneously developing a steering model to help to take decision regarding steering wheel, throttle thus stimulate a car like humans. In this paper, lane detection is the main concern is to move the steering in appropriate direction with proper angle and the problem is solved using convolutional neural networks via creating a model which then is trained over some collected training data of steering decisions on a track in a simulated environment.