My initial thoughts

I got a time series transaction data of purchase logs of different products.

Ex: Product named “Y” purchased for “M” amount, on Date “D” at Location/Place “P” and 5-10 other features.

Now i need to predict, how much we need to pay for purchasing Product named “Y” on new Date “D1” at Location/Place “P1” and same 5-10 other features.

Need inputs on choosing

1. Machine Learning library – I have TensorFlow 2.0 in my mind.

2. ML Model / Neural network arch need to choose – I have Linear Regression in my mind.

3. Training strategy – using TF 2.0

4. Inference/Prediction strategy – using TF 2.0

5. Model saving, loading, versioning. – Saving to / Loading from / versioning using AWS S3.

6. Machine Configuration – Dataset is small so i am Okay with Running on CPU.