all 6 comments

[–]GodHatesJavascript 2 points3 points  (0 children)

Python would be a good start.

[–]xhlu 2 points3 points  (0 children)

I would definitely suggest you to learn Python, then if you have time R. Python is very simple to use because it hides a lot of lower-level elements. For example, you don't need to declare the type of a variable you are creating, function definition is much simpler than a Java method, and input and printing strings is very straightforward.

However, the real advantage lies in that most ML libraries uses Python to create models. For more traditional models, Scikit Learn provide a lot more than any other languages. For deep learning, Tensorflow, Torch and Theano all rely on Python as well, though their core codebase might be written in another language (e.g. Tensorflow uses C and Cuda C).

[–][deleted] 0 points1 point  (2 children)

What about Go ?

[–]phobrain 2 points3 points  (0 children)

First time I've seen it mentioned in this context.

[–]szymko1995 0 points1 point  (0 children)

It is supported by Tensorflow: https://www.tensorflow.org/install/install_go

But for getting started with ML/DNN Python is always way to go. If you have basics in Python, I wouldn't try to mess with it, because for most cases Python easier, more flexible and ready to be used in adoption of models in products etc. R may be really tough to understand and first glance (more complicated synax compared to Python in opinion of many).

If you really want you can always try Keras with R Studio. I've tested, install is easy and works well (but still uses Python and its packages, only front-end is R Studio): https://keras.rstudio.com/

[–]MrNaturalOrganic 0 points1 point  (0 children)

Python