Kaggle Dataset: https://www.kaggle.com/hellbuoy/car-price-prediction General Description: For understanding pricing dynamics of the new market in the different cars for business growth, we will predict the car’s prices depending on different independent variables. Several factors, including mileage,...
Link to the dataset: Kaggle Second-Hand Car Prices DatasetInstallationTo run the project locally, follow these steps:Clone this repository: git clone https://github.com/your-username/second-hand-car-price-prediction.git Install the required dependencies: pip install -r requirements.txt ...
Create a GCP bucket and a BigQuery Dataset with Terraform The GCP bucket will be used to store the data from the car-prices.zip file in a parquet format file. Then the data will be transferred to a BigQuery table which is stored in the created dataset. We will do the transfer with the...
Dataset Link: https://www.kaggle.com/lepchenkov/usedcarscatalog?select=cars.csv Results Overall, PatternSix’s work involved removing the null values for data pre-processing, data exploratory, normality check, finding the correlation between continuous variables, and finding the mean price difference...
Predict the price of a used vehicle
Car Price Dataset: A Comprehensive Collection of Car Prices and SpecificationsData CardCode (8)Discussion (0)Suggestions (0)Oh no! Something went wrong! If the issue persists, it's likely a problem on our side. Unexpected end of JSON inputkeyboard_arrow_downcontent_copySyntaxError: Unexpected ...
we fine-tuned the resulting model on the Autovit.ro dataset for only five epochs to gather the particularities of the Romanian car prices and market. The results presented inTable 7showcased an improvement of over 10% in the R2score for the Autovit.ro validation set after fine-tuning on th...
A simple algorithm such as kNN appears to be adequate for the current competition dataset. KNeighborsRegressor in scikit-learn works too, but is a bit slow. The one in cuml supports uniform weights only. The following implements kNN regression on GPU with inverse distance weighting using the Fa...
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Data context: https://www.kaggle.com/competitions/playground-series-s4e9/overview Overview of the approach My final model was a combination of 9 single models: AutoMLWAlgoDatasetOOF AutoGluon PS4E9 AutoGluon 0,375 LGBM Get Started Used Car Prices 0,198 LGBM LAMA 0,183 Lineral_l2 train+...