Ever wonder what it's like to work at Facebook? Facebook and Kaggle are launching an Engineering competition for 2015. Trail blaze your way to the top of the leader board to earn an opportunity at interviewing for a role as a software engineer, working on world class Machine Learning problems. In this competition, you'll be chasing down robots for an online auction site. Human bidders on the site are becoming increasingly frustrated with their inability to win auctions vs. their software-controlled counterparts. As a result, usage from the site's core customer base is plummeting.
In order to rebuild customer happiness, the site owners need to eliminate computer generated bidding from their auctions. Their attempt at building a model to identify these bids using behavioral data, including bid frequency over short periods of time, has proven insufficient. The goal of this competition is to identify online auction bids that are placed by "robots", helping the site owners easily flag these users for removal from their site to prevent unfair auction activity. The data in this competition comes from an online platform, not from Facebook. Please note: You must compete as an individual in recruiting competitions. You may only use the data provided to make your predictions.
Main-Kernel-Main Scirpt having the exceution of ML and DL model with visualisation and Cleaning(Notebook).Please refer for indepth code and analysis.
H5 files-Deep Learning Keras model
pkl files-Sklearn Machine Learning Model(refer to names for specific classifiers)