FlyingCircus:
First although I have only used R for a few very basic manipulations I believe that it has a full set of ML capabilities. I know they have versions of NN’s, Random Forests and most of the other same toolsets that Python with SciKit-Learn has.

However Kaggle on the Pros and Cons of R vs Python Sci-Kit learn; “In summary, machine learning in R tends to be a more tiresome experience than machine learning in Python once you have moved beyond the basics”.

Before you jump into Scikit-learn. As you said you have written python scripts check out pandas if you haven’t already. Pandas is good for mungeing the data and interface to Scikit-learn. Pandas is just Excel with Visual Basic on steroids.
A little off topic but Wes McKinney was a MIT math grad initially worked in quantitative finance at AQR capital management. In 2008 he wasn’t satisfied with the tools they were using so he started writing pandas and somehow convinced management to allow him to release it as open source. He conceived of pandas and got the ball rolling but at this point over 2000 volunteer contributors have made additions and many corporations have donated either money or their employees time to enhance it.

Wes McKinney has now made the 3rd edition of his Python for Data Analysis available for free at
Python for Data Analysis, 3E (wesmckinney.com)
I bought the paper copy just for convince.

Good Luck

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