This is for non-business use.
I have multiple similar Excel files. They have currently 9 input columns (side by side and in same position) and 1-3 output columns.
Python needs to read these inputs and predict missing outputs and write them to Excel.
I can install whatever you need for Python (I have Anaconda already installed), but I prefer Keras and TensorFlow.
- Read certain Excel file from computer (xlsx). Decimal separators are commas.
- Use certain range of rows and columns (variables) of Excel as training and testing inputs and outputs
- Split the data randomly to training and testing sets
- Ability to tune the neural network (multiple layers, number of neurons per layer, include all hyperparameters (epochs, optimizer, learning rate and momentum, etc))
o Include grid search with printed output for faster neural network optimization
- Ability to select number of outputs for prediction (1 to 3 columns) (this isn't mandatory: 1 is enough, 3 is preferred)
- Automatically selects the output rows (find the first empty row for certain column in Excel and write from there till the end)
- Outputs should be non-binary and decimal separator needs to be comma (for example 0,84234)
- Write the outputs to Excel
- Ability to save network (multiple names for different Excel-files) and load the saved network for endless reuse
I'm a telematics student also, my experience with these type of projects is about 3 years cause it's my work field. Also I'm doing a certification in these programming language.
i am expert on machine learning with tensorflow and keras. i can finish this easily. but i need to know if it is classification or regression. i think we can discuss that soonly.
I am very proficient at Machine Learning using Python, and am capable of reading and outputting information from/into Excel using the Pandas library. I'd be glad to help you with this project.