The real-time bidding (RTB) is vastly growing industry in online advertising where complex and comprehensive algorithms are being utilised to automatically buy and sell the ads to individual users according to their data. This article would analyse technique, algorithms and apply it an altered version of real dataset released by iPinYou. It is suggested that RTB in the United States during 2013 counted for 19% of the total spending in display advertising. Online advertising is growing fast, and RTB is expected to grow signiSicantly. Currently, RTB standard CTR is approximately 0.01% and requires tremendous improvemen. The objective of this report is to evaluate the various techniques and methodologies for the individual part of this coursework that includes (1) Data Exploration (2) Best Bidding Strategy. The report will be based on real-time bidding strategies, exploration and evaluation of dataset provided by an organisation called iPinYou. The report will include how the model being trained evolved its performance. Four dataset Siles will be utilised in order to successfully train the model which include train.csv, test.csv and validation.csv. By training the model, the developed model will evaluate the Click-through rate achieved on the provided dataset. The advertisers carry out an RTB activity through an advertiser exchange to get their adverts displayed on web pages effectively to achieve an impression (an impression is when an advertisement is displayed on a webpage). The end aim of this project is to develop a bidding strategy using the dataset provided which will output best click-through rate.