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A project to predict gasoline prices based on consumer sentiments.

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asadullahqb/GasolinePriceSentimentTimeSeries

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1. Exploratory Data Analysis (EDA).ipynb
1. Exploratory Data Analysis (EDA).ipynb
 
 
2. Data Pre-processing.ipynb
2. Data Pre-processing.ipynb
 
 
3. EDA (post-processing).ipynb
3. EDA (post-processing).ipynb
 
 
4a. Model Building - ARIMAX.ipynb
4a. Model Building - ARIMAX.ipynb
 
 
4aii. Model Building - VAR.ipynb
4aii. Model Building - VAR.ipynb
 
 
4b. Model Building - RNN.ipynb
4b. Model Building - RNN.ipynb
 
 
4c. Model Building - LSTM.ipynb
4c. Model Building - LSTM.ipynb
 
 
4d. Model Building - GRU.ipynb
4d. Model Building - GRU.ipynb
 
 
4e. Model Building - Machine Learning.ipynb
4e. Model Building - Machine Learning.ipynb
 
 
5. Model Comparison and Evaluation.ipynb
5. Model Comparison and Evaluation.ipynb
 
 
README.md
README.md
 
 
Team 7 Time Series (002).pdf
Team 7 Time Series (002).pdf
 
 

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This is a project done for Petronas Data Science Academy Capstone project. It won first place by a landslide victory against other new Data Scientists in the department. The project has been simplified and stripped away of sensitive information, only retaining publicly accessible information and the intellectual property of Asadullah.

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A project to predict gasoline prices based on consumer sentiments.

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