Hacker News new | ask | show | jobs
by drallison 3991 days ago
Machine Learning is a sub-field of computer science and an area of intense current research. It has nothing to do with Python (a programming language) except that some machine learning algorithms might be implemented in Python.

You might find Andrew Ng's Stanford Coursera course a good place to start. https://www.coursera.org/learn/machine-learning/home/info.
2 comments
craigching 3991 days ago
"Introdocution to Statistical Learning" by Trevor Hastie et al. [1] They have a free online class through Stanford [2] Sign in to their system and you can take the archived version for free.

ISL is an excellent, free book, introducing you to ML, you can go deeper, but, to me this is where I wish I'd started. I am taking the Data Science track at Coursera (on Practical Machine Learning now) and I am kicking myself that I didn't start with ISL instead.

Now, I know you specifically asked about Python, but the concepts are bigger than the implementation. All of these techniques are available in Python's ML stack, scikit-learn, NumPy, pandas, etc. I don't know of the equivalent of ISL for Python, but if you learn the concepts and you're a programmer of any worth, you will be able to move from R to Python. Maybe take/read ISL, but do the labs in Python, that might be a fun way to go.

Lastly, to go along with ISL, "Elements of Statistical Learning" also by Hastie et al is available for free to dive deeper [3]

[1] -- http://www-bcf.usc.edu/~gareth/ISL/

[2] -- https://lagunita.stanford.edu/courses/HumanitiesandScience/S...

[3] -- http://statweb.stanford.edu/~tibs/ElemStatLearn/

link
cschmidt 3991 days ago
I also think this is one of the best entry level books, and the Stanford course looks good. This is what I recommend to people. In some ways, R is a very good match for this material, and you could move to python later.
link
cowpig 3991 days ago
Well, you could certainly argue that python has the best machine learning libraries. So it's at worst a relevant programming language to the field.

edit: +1 to Andrew Ng's Coursera course though!

link
sfsylvester 3990 days ago
Was there a reason Ng decided to teach the course in Octave rather than Python? The only time I've ever used .m files was during the course.

I appreciated the challenge of thinking from an array based language, but I felt it held me back from directly comparing my solutions to the tutorials to external sources. (Unless that even in of itself was the reason).

link