Data Science project - Mathematics background required
Budget: $30 – $250 USD
Forecast the households energy consumption for the next six months.
Focus your interest on applying at least three different approaches among the following:
- SVD Applications to PCA.
- Pseudo-Inverse approach.
- Kalman filter.
- Neural networks.
- Exponential Smoothing.
Data may contain measurement errors (0 energy consumption) as missing data you may choose to complete before running your forecasting technique(s).
*REPORT:
Should detail your work methodology, with research references related to the problem, and Discussion section which values the performance of your forecasting technique, using figures and tables. Project should contain the following:
- A PDF report file with the corresponding MS Word, or Latex file source file.
- A forecasting result Datafile: .csv, .txt, xlsx, or any other.
- Any code you have used to realize your project
Data size: 1100 row
Focus your interest on applying at least three different approaches among the following:
- SVD Applications to PCA.
- Pseudo-Inverse approach.
- Kalman filter.
- Neural networks.
- Exponential Smoothing.
Data may contain measurement errors (0 energy consumption) as missing data you may choose to complete before running your forecasting technique(s).
*REPORT:
Should detail your work methodology, with research references related to the problem, and Discussion section which values the performance of your forecasting technique, using figures and tables. Project should contain the following:
- A PDF report file with the corresponding MS Word, or Latex file source file.
- A forecasting result Datafile: .csv, .txt, xlsx, or any other.
- Any code you have used to realize your project
Data size: 1100 row