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Healthcare fraud detection using machine learning | Data Science Blog
Introduction Healthcare fraud is a major concern for healthcare providers, insurers and governments worldwide. It involves illegal activities, such as billing for services that were not provided, duplicate submission of a claim for the same service, misrepresenting the service provided, charging for a more complex or expensive service than was provided or billing for a
Injury Analysis of Soccer Players with Python | Alexandra Melville
Presentation Video Introduction Sports are an integral part of many people's lives. For some sports are something to bet on, and for others fantasy leagues become an obsession. Then there’s the category I’m a part of: the die-hard fan. Given my interest in sports, I thought it would be fun to explore data from the
Predicting Home Prices with Machine Learning Predicting Home Prices with Machine Learning | Data Science Blog
Predicting Home Prices with Machine Learning Introduction Buying or selling a home is one of the most significant financial decisions people make. Accurately predicting home prices is essential for buyers, sellers, and real estate professionals to make informed choices. Machine learning provides a powerful tool to enhance accuracy in home price estimation. In this blog,
Sentiment-Enhanced Product Recommendation System for E-Commerce | Data Science Blog
Overview This project applies advanced Natural Language Processing (NLP) techniques to analyze customer sentiment in e-commerce product reviews. By extracting emotional context from user-generated content, the system creates a much improved recommendation engine that goes beyond traditional rating systems. The implementation compares two leading sentiment analysis approaches—RoBERTa (an optimized BERT variant) and VADER—to determine which
Predicting the Unpredictable: Revolutionizing E-commerce Delivery with Machine Learning | Data Science Blog
Introduction In today's hyper-competitive e-commerce landscape, delivery time has emerged as a critical differentiator for customer satisfaction and retention. Yet accurately predicting delivery timelines remains one of the industry's most challenging problems due to the complex interplay of geography, logistics, product characteristics, and temporal patterns. Through an extensive machine learning implementation utilizing the Olist e-commerce
Wine Purchasing Trends: A Data-Driven Analysis of Customer Behavior | Data Science Blog
Introduction This project explores wine purchasing patterns in e-commerce, examining how customer demographics, income levels, and shopping channel preferences influence buying decisions. Through Python-based analysis and visualization, this study aims to provide actionable insights for optimizing wine retail strategies. Dataset Overview The analysis leverages a comprehensive dataset of 2,240 customer records across 29 variables, providing
Exploring Tarisio Stringed Instrument and Bow Auction Data | Data Science Blog
Introduction The goal of this project was to design a Shiny dashboard that analyzes a real-world dataset using Python. As a professional violinist, I wanted to leverage my domain knowledge and interests and chose to use stringed instrument and bow auction data from Tarisio.com for my project. Tarisio is an auction house with the largest
Machine Learning for Predicting Housing Prices in Ames, Iowa | Data Science Blog
Introduction Purchasing a home is a significant life decision. Since a mortgage lasts for decades and often represents the most considerable debt in a person’s lifetime, this decision carries immense financial implications. Given how consequential a home purchase is for an individual’s economic well-being, it is essential to be as well-informed as possible about the
| Data Science Blog
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R Project: E-Commerce Customer Behavior | Data Science Blog
Introduction This project aims to help businesses better understand what their customers want and what incentivizes them to place an order. By leveraging this information, business owners can offer the products, services, and associated incentives that will not only attract customers but also convert them into loyal buyers. Furthermore, the insights gained from this analysis Oreste RUKUNDO December 20, 2024 Introduction This project aims to help businesses better understand what their customers want and what incentivizes them to place an order. By leveraging this information, business owners can offer the products, services, and associated incentives that will not only attract customers but also convert them into loyal buyers. Furthermore, the insights gained from this analysis
Lending Club Dataset Analysis | Data Science Blog
Lending Club Dataset Analysis: Insights for Investors Author: Hunter DeRouen Date: October 2024 Introduction As part of the NYC Data Science Academy Bootcamp, this project explores key insights from the Lending Club dataset. Lending Club is a peer-to-peer lending platform that allows individuals to lend money directly to other individuals, creating a direct connection between
Clustering Artworks by Ai-Quantified Visual Qualities & Content Recommendation App | Data Science Blog
By Gabriel del Valle 10/08/24 www.linkedin.com/in/gabrielxdelvalle Introduction One of the most transformative ways that Data Science has brought value to major web platforms like Amazon and Spotify is modeling user preferences to make recommendations which the user finds relevant. For content driven platforms like TikTok or Meta, the quality of their recommendation algorithm is
Forecasting NY State Tax Credits: R Shiny App for Businesses
Introduction Background Many New York State corporations find it worthwhile to investigate tax laws to determine possible credit eligibility under Article 9-A (Franchise Tax on Business Corporations) of the New York State Tax Law. As mandated by the Business Tax Reform and Rate Reduction Act of 1987 Section 109(a), all corporations (except LLCs, Subchapter S
US Honey Production Analysis With Python (1998-2012) | Data Science Blog
Introduction One of the things I like most about living in Eastern Washington is gardening. While I enjoy growing produce and flowers for myself, I also think about what will attract bees. They serve a vital function for gardeners as pollinators. Also seeing swarms of bees on a hot summer day and listening to their
Python EDA Project : Salary Prediction. | Data Science Blog
Introduction: Salary prediction is a crucial application of machine learning and statistical modeling that aims to estimate the salary of an individual based on various factors like age, education, and experience. Accurate salary predictions are valuable for job seekers, employers, and policymakers. The objective of this project is to analyze factors affecting salary predictions. I explored
Moneyball for Movies | Data Science Blog
Link to the project https://christopherwilson.shinyapps.io/hello_shiny/ Link to github https://github.com/jackparsons93/r_shiny_imdb_movies Say, you want to produce a movie. What can you do to put the odds of success in your favor? You can look at the features of other successful movies and then plan to apply them to the one you’re producing. That’s the goal of
The quest for R^2 ROI on Home Improvements | Data Science Blog
Link to GitHub https://github.com/jackparsons93/Ames_Housing_ML As a house is often the biggest purchase many of us will make, we want to be certain about its value and be strategic about improvements we make with the intent to sell at a profit. Using the Kaggle Ames Housing set, I applied machine learning with the aim of
Music Analysis with Python | Data Science Blog
Chris Wilson Link To Github https://github.com/jackparsons93/music_project As someone trained in classical music, I sought to apply data science to that discipline using Python. I used it to explore two questions about composition and to develop a motif detector. For this project, I referred to works by Bach, Mozart, and Beethoven. The questions I
Building a Titanic Classifier with End-to-End Machine Learning Pipeline | Data Science Blog
In this blog post, I’ll guide you through the creation of an end-to-end machine learning pipeline using the Titanic dataset. This project was developed as part of a technical interview, focusing on data exploration, preprocessing, model selection, evaluation, and deployment. Additionally, the project ideation includes a fully automated model training and selection pipeline that streamlines
TwilioGPT modernizing telephone and voice systems using LLMs and NLP | Data Science Blog
By Chris Wilson Link to Github https://github.com/jackparsons93/RAG_to_riches This is the blog for my capstone project using sound recognition and the Twilio API along with the OpenAI API to create interactive voice assistants. The first chatbot in my presentation uses a script called twilly.py. Twilly.py is a very primitive chatbot that uses ChatGPT to answer
NYC Animated Traffic Maps and Branch Analysis | Congestion Zone | Congestion Zone
NYC Animated Traffic Maps and Branch Analysis July 28th 2024 By Gabriel del Valle www.linkedin.com/in/gabrielxdelvalle Introduction A sweeping economic change looms over Manhattan, creating new considerations for all manner of businesses and workers alike, until... On June 5 2024, in the final hours before Manhattan's Congestion Relief Zone became law -- the policy
Modeling Valuation Multiples of Companies with Gradient Boost | Data Science Blog
Motivation The main goal of a financier in investment management is to build and manage a portfolio with a strong return on investment that ideally outperforms the market. One of the most central concepts to constructing robust stock portfolios is relative valuation. That is looking at how a publicly traded company is valued compared to