GitHub - KrishBakshi/Time-series-sales-forcating-using-XgBoost: Time series analysis and forcasting using Pyspark and Gradient boosting algorithms. The dataset consists prooducts and their corresponding information on its sales with respect to different stores, discounts and other factors in the dataset. The goal is to make a model to accuately predict sales with minimum error.

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Time series analysis and forcasting using Pyspark and Gradient boosting algorithms. The dataset consists prooducts and their corresponding information on its sales with respect to different stores, discounts and other factors in the dataset. The goal is to make a model to accuately predict sales with minimum error.

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Name		Name	Last commit message	Last commit date
Latest commit History 12 Commits
.ipynb_checkpoints		.ipynb_checkpoints
dataset		dataset
.gitattributes		.gitattributes
Base XGBoost sales forcasting model.ipynb		Base XGBoost sales forcasting model.ipynb
EDA_Promotional_sales_product_id_10184270.ipynb		EDA_Promotional_sales_product_id_10184270.ipynb
Entire data pipeline.py		Entire data pipeline.py
Promotional_sales_productID_10005752.ipynb		Promotional_sales_productID_10005752.ipynb
Promotional_sales_product_id_10184270.ipynb		Promotional_sales_product_id_10184270.ipynb
Xgboost pipeline.ipynb		Xgboost pipeline.ipynb