A commany has recently introduced a new type of bidding, the average bidding, as an alternative to the bid given to the current maximum bidding

Overview

image

Business Problem

A commany has recently introduced a new type of bidding, the average bidding, as an alternative to the bid given to the current maximum bidding. One of our clients, bombabomba.com, decided to test this new feature and would like to do an A/B test to see if average bidding converts more than maximum bidding.

  • Maximum Bidding (Control Group)
  • Average Bidding (Test Group)

Dataset Description

This dataset, which contains the website information of bombabomba.com, there is information such as the number of advertisements that users see and click, as well as earnings information from here. There are two separate data sets, the control and test groups.

Variables

  • Impression – Ad views
  • Click – (Indicates the number of clicks on the displayed ad.)
  • Purchase - (Indicates the number of products purchased after the ads clicked.)
  • Earning - (Earnings after purchased products)

My Kaggle Notebook

Owner
Kübra Bilinmiş
Data Science and Machine Learning Enthusiast
Kübra Bilinmiş
Model Serving Made Easy

The easiest way to build Machine Learning APIs BentoML makes moving trained ML models to production easy: Package models trained with any ML framework

BentoML 4.4k Jan 08, 2023
Distributed Evolutionary Algorithms in Python

DEAP DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data stru

Distributed Evolutionary Algorithms in Python 4.9k Jan 05, 2023
Mixed Transformer UNet for Medical Image Segmentation

MT-UNet Update 2021/11/19 Thank you for your interest in our work. We have uploaded the code of our MTUNet to help peers conduct further research on i

dotman 92 Dec 25, 2022
An educational AI robot based on NVIDIA Jetson Nano.

JetBot Looking for a quick way to get started with JetBot? Many third party kits are now available! JetBot is an open-source robot based on NVIDIA Jet

NVIDIA AI IOT 2.6k Dec 29, 2022
GNN-based Recommendation Benchma

GRecX A Fair Benchmark for GNN-based Recommendation Preliminary Comparison DiffNet-Yelp dataset (featureless) Algo 73 Oct 17, 2022

Predict multi paths to a moving person depending on his trajectory history.

Multi-future Trajectory Prediction The project is about using the Multiverse model to make possible multible-future trajectory prediction for a seen p

Said Gamal 1 Jan 18, 2022
[SIGGRAPH Asia 2019] Artistic Glyph Image Synthesis via One-Stage Few-Shot Learning

AGIS-Net Introduction This is the official PyTorch implementation of the Artistic Glyph Image Synthesis via One-Stage Few-Shot Learning. paper | suppl

Yue Gao 102 Jan 02, 2023
MHFormer: Multi-Hypothesis Transformer for 3D Human Pose Estimation

MHFormer: Multi-Hypothesis Transformer for 3D Human Pose Estimation This repo is the official implementation of "MHFormer: Multi-Hypothesis Transforme

Vegetabird 281 Jan 07, 2023
PyTorch implementation of residual gated graph ConvNets, ICLR’18

Residual Gated Graph ConvNets April 24, 2018 Xavier Bresson http://www.ntu.edu.sg/home/xbresson https://github.com/xbresson https://twitter.com/xbress

Xavier Bresson 112 Aug 10, 2022
Contrastive Loss Gradient Attack (CLGA)

Contrastive Loss Gradient Attack (CLGA) Official implementation of Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation, WWW22 Bu

12 Dec 23, 2022
Parametric Contrastive Learning (ICCV2021)

Parametric-Contrastive-Learning This repository contains the implementation code for ICCV2021 paper: Parametric Contrastive Learning (https://arxiv.or

DV Lab 156 Dec 21, 2022
Implementation of algorithms for continuous control (DDPG and NAF).

DEPRECATION This repository is deprecated and is no longer maintaned. Please see a more recent implementation of RL for continuous control at jax-sac.

Ilya Kostrikov 288 Dec 31, 2022
Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning (ICLR 2021)

Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning (ICLR 2021) Citation Please cite as: @inproceedings{liu2020understan

Sunbow Liu 22 Nov 25, 2022
Torchreid: Deep learning person re-identification in PyTorch.

Torchreid Torchreid is a library for deep-learning person re-identification, written in PyTorch. It features: multi-GPU training support both image- a

Kaiyang 3.7k Jan 05, 2023
Speedy Implementation of Instance-based Learning (IBL) agents in Python

A Python library to create single or multi Instance-based Learning (IBL) agents that are built based on Instance Based Learning Theory (IBLT) 1 Instal

0 Nov 18, 2021
text_recognition_toolbox: The reimplementation of a series of classical scene text recognition papers with Pytorch in a uniform way.

text recognition toolbox 1. 项目介绍 该项目是基于pytorch深度学习框架,以统一的改写方式实现了以下6篇经典的文字识别论文,论文的详情如下。该项目会持续进行更新,欢迎大家提出问题以及对代码进行贡献。 模型 论文标题 发表年份 模型方法划分 CRNN 《An End-t

168 Dec 24, 2022
Pytorch implementation for "Open Compound Domain Adaptation" (CVPR 2020 ORAL)

Open Compound Domain Adaptation [Project] [Paper] [Demo] [Blog] Overview Open Compound Domain Adaptation (OCDA) is the author's re-implementation of t

Zhongqi Miao 137 Dec 15, 2022
Official Keras Implementation for UNet++ in IEEE Transactions on Medical Imaging and DLMIA 2018

UNet++: A Nested U-Net Architecture for Medical Image Segmentation UNet++ is a new general purpose image segmentation architecture for more accurate i

Zongwei Zhou 1.8k Jan 07, 2023
A tutorial on DataFrames.jl prepared for JuliaCon2021

JuliaCon2021 DataFrames.jl Tutorial This is a tutorial on DataFrames.jl prepared for JuliaCon2021. A video recording of the tutorial is available here

Bogumił Kamiński 106 Jan 09, 2023
[NeurIPS2021] Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks

Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Code for NeurIPS 2021 Paper "Exploring Architectural Ingredients of A

Hanxun Huang 26 Dec 01, 2022