GitHub - RPf357/Group-4-Time-Series-Forecasting: Store sales forecasting using time series forecasting is a data-driven approach that utilizes historical sales data to predict future sales trends. By analyzing patterns, seasonality, and other temporal factors in the data, businesses can make informed decisions about inventory management, staffing, and marketing strategies.

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Store sales forecasting using time series forecasting is a data-driven approach that utilizes historical sales data to predict future sales trends. By analyzing patterns, seasonality, and other temporal factors in the data, businesses can make informed decisions about inventory management, staffing, and marketing strategies.

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Name		Name	Last commit message	Last commit date
Latest commit History 13 Commits
.gitattributes		.gitattributes
Lstm (3).ipynb		Lstm (3).ipynb
app.py		app.py
future_sales_by_family.html		future_sales_by_family.html
holidays_events.csv		holidays_events.csv
index.html		index.html
model.pkl		model.pkl
model.py		model.py
my_model.h5		my_model.h5
oil.csv		oil.csv
prediction.html		prediction.html
sales_forecasting_arima_model (1).ipynb		sales_forecasting_arima_model (1).ipynb
stores.csv		stores.csv
styles.css		styles.css
test.csv		test.csv
train.csv		train.csv
transactions.csv		transactions.csv