Topic: "gradient-boosting-regression"
silverrainb/bitcoin-price-pred
Predict bitcoin price using gold and S&P 500 data implementing LSTM, Gradient Boosting Regression, and Random Forest
Language: HTML - Size: 11.8 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 7 - Forks: 4
dharmikbanka23/Insurance-Product-Purchase-Prediction
This project aims to develop a predictive model estimating insurance coverage costs for customers based on their attributes and product choices. The dataset includes transaction and quote details for policy purchasers. The objective is to predict quoted coverage costs, considering customer traits and 7 customizable product options.
Language: Jupyter Notebook - Size: 2.67 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0
charumakhijani/advanced-house-price-prediction
Language: Jupyter Notebook - Size: 1.66 MB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 1
yyigitturan/Baseball-Players-Salary-Prediction
This project develops a machine learning model to predict the salaries of baseball players based on their past performance.
Language: Python - Size: 803 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0
am-tropin/poland-apartment-prices
🇵🇱🏠 The project predicts an apartment price for Warsaw, Krakow and Poznan. Distributed apartments by districts using geopandas; built XGBoost model with MAPE = 9% (the best of others).
Language: Jupyter Notebook - Size: 78.9 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0
jcatanza/gradient_boosting_regression
In this notebook, we'll build from scratch a gradient boosted trees regression model that includes a learning rate hyperparameter, and then use it to fit a noisy nonlinear function.
Language: HTML - Size: 1020 KB - Last synced at: almost 2 years ago - Pushed at: almost 5 years ago - Stars: 0 - Forks: 0
