项目作者: PriyabrataThatoi

项目描述 :
Zbay's CTR Prediction using Python & H20 AutoML. Zbay's is an e-commerce website. Users log in to their website and purchases the item. However, there are times, when users didn't make any purchases. Instead they go their competitors. In order to bring them back and make them purchases, Zbay's utilizes third-party to create ads on their website and redirect users to their website. In this project, the task is to predict the CTR probability on such ads
高级语言: Jupyter Notebook
项目地址: git://github.com/PriyabrataThatoi/ZBay-CTR-Prediction.git
创建时间: 2019-09-05T17:49:32Z
项目社区:https://github.com/PriyabrataThatoi/ZBay-CTR-Prediction

开源协议:

下载


WNS ANALYTICS CHALLENGE :

“PREDICTING CLICK THROUGH RATE FOR THE ZBAY’S ADVERTISMENTS”
wns1

PROBLEM STATEMENT

Zbay is an E-commerce website which sells a variety of products at its online platform. Zbay records user behaviour of its customers and stores it as a log. However, most of the times, users do not buy the products instantly and there is a time gap during which the customer might surf the internet and maybe visit competitor websites. Now, to improve sales of products, Zbay has hired Adiza, an Adtech company which built a system such that ads are being shown for Zbay’s products on its partner websites. If a user comes to Zbay’s website and searches for a product, and then visits these partner websites or apps, his/her previously viewed items or their similar items are shown on as an ad. If the user clicks this ad, he/she will be redirected to the Zbay’s website and might buy the product.

problem statement

OBJECTIVE

The task is to predict click probability i.e. probability of user clicking the ad which is shown to them on the partner websites for the next 7 days on the basis of historical view log data, ad impression data and user data

DATA

view log of users (2018/10/15 - 2018/12/11) and the product description collected from the Zbay website. We also provide the training data and test data containing details for ad impressions at the partner websites(Train + Test). Train data contains the impression logs during 2018/11/15 – 2018/12/13 along with the label which specifies whether the ad is clicked or not. Your model will be evaluated on the test data which have impression logs during 2018/12/12 – 2018/12/18 without the labels

Train File : https://datahack.analyticsvidhya.com/contest/wns-analytics-wizard-2019/download/train-file

Test File : https://datahack.analyticsvidhya.com/contest/wns-analytics-wizard-2019/download/test-file

TECHNOLOGY USED

Python, H20 AUTOML

PRIVATE LEADERBOARD

Public LB : 364th/6456 Rank