Tag: Linear Regression
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Python Data Science for Real Estate & REIT Amsterdam: (Auto) EDA, NLP, Maps & ML
The Amsterdam real estate market has experienced a significant resurgence, with property prices increasing by double digits annually since 2013. Data science is being used to analyze the city’s housing and rental markets, revealing insights on the impact of Airbnb and empowering communities with the necessary information. Comprehensive data analysis and machine learning techniques are…
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A Balanced Mix-and-Match Time Series Forecasting: ThymeBoost, Prophet, and AutoARIMA
The post evaluates the performance of popular Time Series Forecasting (TSF) methods, namely AutoARIMA, Facebook Prophet, and ThymeBoost on four real-world time series datasets: Air Passengers, U.S. Wholesale Price Index (WPI), BTC-USD price, and Peyton Manning. Each TSF model uses historical data to identify trends and make future predictions. Studies indicate that ThymeBoost, which combines…
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Gold Price Linear Regression
This content focuses on predicting gold prices using machine learning algorithms in Python. With an 80% R2-score and a Sharpe ratio of 2.33, it suggests a potential 8% revenue from an investment starting in December 2022. The forecasted next-day price for SPDR Gold Trust Shares is $185.136, aligning with Barchart’s “100% BUY” signal.
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Real Estate Supervised ML/AI Linear Regression Revisited – USA House Price Prediction
ETL Workflow Linear regression is an algorithm of supervised Machine Learning (ML) in which the predicted output is continuous with having a constant slope [1]. Consider a company of real estate with datasets containing the property prices of a specific region. The price of a property is based on essential factors like bedrooms, areas, and…
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