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Commodity-Price-Prediction
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Commodity-Price-Prediction
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# Commodity-Price-Prediction ### Description - Commodity price prediction project has been used to predict the future forecast price from the past 5 years commodities prices. - The project contains the database of data built with SQL. The database is built with SQL tables from CSV files to provide secure storage. - An interactive GUI is built to provide easy access in project. The easily determined GUI can be used to execute the program efficiently. - Two models has been used to predict future prices. ARIMA is a statistical approach to predict future price, has been used for short term forecast of 6 days. RNN-LSTM is a sequence modelling deep learning technique to forecast future price for long-term predictions of 30 days. - The GUI has provided the ability in it to execute both the models as per your future price predcition choice. ### Technologies Used Data Analysis, Data Mining, Deep Learning, Databases. #### Python Libraries Numpy, Pandas, Scipy, Sklearn, Keras, Tensorflow, Pickle. #### Database MySQL. #### Interface TkInter, Pygame #### Requirements ``` python 3 pip3 Tensorflow-GPU ``` ### Publication + This is a Research Based Project, Completed at [CDAC-Banaglore](https://www.cdac.in/index.aspx?id=bangalore) and **In the 7th International Conference on Big Data Analytics, BDA 2019, at Ahmedabad, India on December 17–20, 2019, the research paper has been published with the title "Market Intelligence for Agricultural Commodities Using Forecasting and Deep Learning Techniques."** [Springer-Link](https://link.springer.com/chapter/10.1007/978-3-030-37188-3_12) Thank you for visiting. Don't forget to give a star!!
