To run the model:
python main.py
Submit a pdf describing:
- The Data Set (2 marks) a. Visualisation of some of the key attributes is necessary for a top grade b. Any pre-processing such as normalisation applied to the data
- The network structure and other hyperparameters (2 marks).
- The Cost / Loss / Error / Objective function (1 mark).
- The optimiser (1 mark).
- Cross Fold Validation (2 marks).
- Results โ accuracy and/or precision and/or recall (2 marks). a. Include plots if opting for a top grade.
- Evaluation of the results (2 marks).
- Impact of varying a hyperparameter(s) (3 marks)
Submit a Jupyter notebook with the code where:
- The book is named CS4287-Prj1-ID1-ID2
- Where ID1 and ID2 are the student id numbers of the team members
- The first line in the book is a comment with names and ID numbers of the team members
- The second line in the book should be a comment stating if the code executes to the end without an error.
- The third line in the book should be a comment with a link to the original source where you opted to reuse an existing implementation.
- Every critical line of code MUST be commented by YOU. To demonstrate a deep understanding of that code.
Hand written numbers (minst) Shannon airport weather data
- Read the dataset into python
- (Maybe?) Divide date into separate fields for year / month / day
- Normalize data