I want to do my first beginner-level project regarding Data Science. I picked my data set which is described below. I want to make a Python script which will make some predictions on our data set using training and test data. That could be for example a prediction which countries will see rise in number of customers and which ones will see a decline, but that's just the first idea that popped in my head. I want to implement a few Machine Learning methods to do the same prediction on our data set and compare their results. Finally comes my question - which Machine Learning methods would you suggest for a beginner Data Science project with this data set which is described below? Thank you in advance for any suggestions. I don't want to pick something very hard as the beginner and I also don't want to pick a method that just doesn't "fit" my data set (because it's rather simple).
EDIT: To specify this project will concern business predictions based probably on time-series. I'm looking for recommendations for which ML methods are easy to implement use and understand for the beginner. Project will be written in Python.
Data Set Description:
Number of Attributes : 8
Invoice : Integer
StockCode : String
Quantity : Integer
InvoiceDate : Timestamp
Price : Decimal
CustomerID : Integer
Country : String
Number of records: 541910
Date ranges: 01/12/2010 08:26 - 09/12/2011 12:50
Price ranges: -11062.06 - 38970.00
Number of distinct Countries: 38