Topic: uplift-modeling Goto Github
Some thing interesting about uplift-modeling
Some thing interesting about uplift-modeling
uplift-modeling,Machine learning based causal inference/uplift in Python
User: andrewtavis
uplift-modeling,DSND Term 2 Portfolio Exercise: Optimize promotion offers for Starbucks
User: andypwyu
uplift-modeling,This repository provides a platform for the predicting of future stock prices based on historical stock prices. Time series analysis is extensively explored in this project. The repository also contains pipelines that can be reused for analyzing and predicting stock prices and feature extraction.
User: basseyisrael
uplift-modeling,
User: carjung
uplift-modeling,YLearn, a pun of "learn why", is a python package for causal inference
Organization: datacanvasio
Home Page: https://ylearn.readthedocs.io
uplift-modeling,因果推理&AB实验相关论文小书库
User: dsxiangli
uplift-modeling,Lightweight uplift modeling framework for Python
User: duketemon
Home Page: https://pyuplift.readthedocs.io
uplift-modeling,Analysing promotion effectiveness on Starbucks' reward mobile app
User: fanfanyjs
uplift-modeling,My collection of causal inference algorithms built on top of accessible, simple, out-of-the-box ML methods, aimed at being explainable and useful in the business context
User: gdmarmerola
uplift-modeling,A flexible python package for cost-aware uplift modelling.
Organization: google-marketing-solutions
uplift-modeling,train models in pytorch, Learn to Rank, Collaborative Filter, Heterogeneous Treatment Effect, Uplift Modeling, etc
User: haowei01
uplift-modeling,Uplift Modeling to identify the pursuable group of users from all the users in order to send them encouragement (in terms of coupons or other offers) to buy the product more without spending resources to convert those users who are not willing or interested to buy the product even after encouragement.
User: imnikhilanand
uplift-modeling,This repository consists of predicting dynamic pricing, churn predictions using sales and marketing data for understanding users' behaviour.
User: imsanjoykb
Home Page: https://imsanjoykb.github.io/
uplift-modeling,🛠 How to Apply Causal ML to Real Scene Modeling?How to learn Causal ML?【✔从Causal ML到实际场景的Uplift建模】
User: jackhcc
uplift-modeling,A powerful tree-based uplift modeling system.
Organization: jd-opensource
uplift-modeling,A Python Framework for Automatically Evaluating various Uplift Modeling Algorithms to Estimate Individual Treatment Effects
User: jroessler
uplift-modeling,Implementation of paper DESCN, which is accepted in SIGKDD 2022.
User: kailiang-zhong
uplift-modeling,Posts covering different causal inference topic.
User: leowu4ever
Home Page: https://leowu4ever.github.io/causal-inference-items/
uplift-modeling,:exclamation: uplift modeling in scikit-learn style in python :snake:
User: maks-sh
Home Page: https://www.uplift-modeling.com
uplift-modeling,Advanced Microeconomics final project for DSE
User: mathicard
uplift-modeling,A modified uplift modeling technique to convert "treatment nonresponders" to "responders" is proposed through multifaceted interventions in market campaigns.
User: mazba-ahamad
uplift-modeling,study about causality
User: minsoo9506
uplift-modeling,CausalLift: Python package for causality-based Uplift Modeling in real-world business
User: minyus
Home Page: https://causallift.readthedocs.io/
uplift-modeling,smote meets uplift modeling
User: mnlscn
uplift-modeling,This contains projects based on Algorithmic Marketing like Marketing Mix Modeling, Attribution Modeling & Budget Optimization, RFM Analysis, Customer Segmentation, Recommendation Systems, and Social Media Analytics
User: nikhilkohli1
uplift-modeling,Algorithmic Marketing based Project to do Customer Segmentation using RFM Modeling and targeted Recommendations based on each segment
User: nikhilkohli1
uplift-modeling,Uplift modeling and evaluation library. Actively maintained pypi version.
User: rsyi
Home Page: https://docs.pylift.org/
uplift-modeling,Customer targeting model to optimize promotion targeting, on simulated data from Starbucks. (work in progress)
User: tamasdinh
uplift-modeling,Marketing Analytics project : Promotion email targeting with uplift and causal forest model
User: tongxinguo
uplift-modeling,Uplift modeling and causal inference with machine learning algorithms
Organization: uber
uplift-modeling,Statistical analysis to see effectiveness of email marketing campaign. Used regression, DoWhy & CausalML to calculate treatment effects. Feature importance & CATE, ITEs.
User: uzairahmadxy
uplift-modeling,An ensemble is based on the notion of combining models. While uplift modeling combines supervised modeling with A-B testing, which is a simple type of randomized experiment.
User: villagomez-joshi-cloud
uplift-modeling,Causal Simulations for Uplift Modeling
Organization: vub-dl
uplift-modeling,https://arxiv.org/abs/2009.01561
User: zahradbozorgi
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