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[BA project] Dynamic Pricing Optimization for Airbnb listing to optimize yearly profit for host. Use Clustering for competitive analysis, kNN regression for demand forecasting, and find dynamic optimal price with Optimization model.
Forecasting of ATM Withdrawals to improve efficiency of ATM Replenishment
Multivariate Time Series Forecasting with LSTM
Practice Problem provided by Analytics Vidya to predict the purchase price by a customer on Black Friday
Customer Segmentation, RFM analysis and price elasticity
INFO7374 - 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
This is the HyperGo algorithm introduced in paper "E-tail Product Return Prediction via Hypergraph-based Local Graph Cut" published in KDD 2018
Python code for common Machine Learning Algorithms
Customer segmentation was performed using hierarchial clustering, K-means clustering, and K-means with Principle Component Analysis and observed four main segments of customers in the data. With the help of logistic regression and price elasticity, I identified the tipping point of each of the segments and their contribution to the revenue. Further, I used multi-nominal logistic regression and understood the product choice of each of the segment. I then applied cross-price elasticity to gather insights between all the products and how it affects each of the segments with price range and promotions. I concluded the project by drawing product management and customer satisfaction suggestions.
While the rate of fatal road accidents has been decreasing steadily since the 80s, the past ten years have seen a stagnation in this reduction. Coupled with the increase in number of miles driven in the nation, the total number of traffic related-fatalities has now reached a ten year high and is rapidly increasing. By looking at the demographics of traο¬c accident victims for each US state, we find that there is a lot of variation between states. Now we want to understand if there are patterns in this variation in order to derive suggestions for a policy action plan. In particular, instead of implementing a costly nation-wide plan we want to focus on groups of states with similar profiles. How can we find such groups in a statistically sound way and communicate the result effectively? This project lets you apply skills from: Introduction to Shell for Data Science, including how to navigate the file system and view files pandas Foundations, including reading, exploring, filtering, and grouping data Manipulating DataFrames with pandas, including how to reshape data into the long format and how to perform multiple aggregations Merging DataFrames with pandas, including how two merge two DataFrames Unsupervised Learning in Python, including KMeans clustering, dimensionally reduction through PCA, and visualizations using matplotlib Supervised Learning with scikit-learn, including multivariate regression Intermediate Python for Data Science, including visualizations using matplotlib Data Visualization With Seaborn, including statistical visualizations using seaborn
price elasticity
Predicting Convenience Store Shrink
This is a system that predicts the time series of cash withdrawals at ATMs using Holt-Winters, RNN LSTM, SSA and optimizing cash management strategies using a discrete optimal control system.
This is a repo for all the time series related notebook for AIENgineering
ATM Forecast
A declarative, efficient, and flexible JavaScript library for building user interfaces.
π Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. πππ
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google β€οΈ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.