Popular GitHub Repositories for Revenue Uplift

Uplift modeling and causal inference with machine learning algorithms

Ssebowa is an open-source generative AI platform offering free access to powerful AI models for everyone. Use 100% of revenue got from ads and apis to plant trees and give meals to children in need. Think of us as the ChatGPT4 that serves humanity!

Machine learning based causal inference/uplift in Python

Movie Recommendation Chatbot provides information about a movie like plot, genre, revenue, budget, imdb rating, imdb links, etc. The model was trained with Kaggle’s movies metadata dataset. To give a recommendation of similar movies, Cosine Similarity and TFID vectorizer were used. Slack API was used to provide a Front End for the chatbot. IBM Watson was used to link the Python code for Natural Language Processing with the front end hosted on Slack API. Libraries like nltk, sklearn, pandas and nlp were used to perform Natural Language Processing and cater to user queries and responses.

Sales Conversion Optimization MLOps: Boost revenue with AI-powered insights. Features H2O AutoML, ZenML pipelines, Neptune.ai tracking, data validation, drift analysis, CI/CD, Streamlit app, Docker, and GitHub Actions. Includes e-mail alerts, Discord/Slack integration, and SHAP interpretability. Streamline ML workflow and enhance sales performance.

Smart Contract and Tokenization Framework for Africa Fast Ferry Ltd Compliant with SEC Regulation D Rule 506(c) and Regulation S — Combining Regulated Equity (AFFEQ) and Revenue-Sharing (AFFR) Tokens based on ERC-3643 Standards.

This Machine Learning project deals with Coupon Recommendations based on Revenue Uplift

Build a predictive machine learning model that could categorize users as either, revenue generating, and non-revenue generating based on their behavior while navigating a website. In order to predict the purchasing intention of the visitor, aggregated page view data kept track during the visit along with some session is used and user information as input to machine learning algorithms. Oversampling/Undersampling and feature selection techniques are applied to improve the success rates and scalability of the models.

Model that uses 10 different algorithms to predict the revenue of a movie before it's release

An MLOps pipeline for optimizing game discount strategies using Steam reviews, tags, and competitor pricing. Designed for data-driven revenue maximization in the gaming industry.

Mars IO – Mentality-Based Anime Recommendation System AI-Powered Motivation Through Anime Mars IO is an intelligent, psychology-inspired anime recommendation system designed to uplift users based on their current emotional and mental state. By integrating AI and mental health awareness, it suggests anime that aligns with the user's mood—helping.

Revenue Modelling and Forecasting | Online Retail II UCI Dataset | Kaggle

A model try to predict the revenue for hotels based on data in real life (real data)

The goal of this project is to build a machine learning model to predict customer churn for Camtel ?, a major telecommunications provider. Customer churn—the rate at which customers leave the service—is a key challenge that directly impacts revenue ? and business stability ?.

Time series analysis of Mercado Libre that uses Prophet ML models to forecast Google search traffic and future revenue

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.

Recommender systems became one of the essential areas in the machine learning field. Product recommendations are key to enhance customer exeperiance and help them to find the right product from huge corpus of products. When customer find the right product that are mostly like going to add the item to cart and which help in company revenue.

Analyzes clickstream data from an e-commerce platform to predict customer conversions, estimate potential revenue, and segment users for personalized marketing strategies. By leveraging machine learning techniques, the project enhances decision-making for businesses seeking to optimize user engagement and sales.

Predicting the Advertisement Revenue for a auction website along with setting the range of bidding values for next auctions.

Customer Churn Prediction for improving customer retaining and reduce revenue loss: