[BangPypers] Resource for ML

[Arjunil Pathak]

I can vouch for Coursera's ML courses by University of Washington.

It gives you a brief overview of the possibilities ML presents in the
foundations course - predictive models using regression,  document
classification, recommender systems in the very first course - good for
whetting your appetite with a black box approach. The next courses delve
deep into each example, be it Regression, or Classification - with generous
doses of math(some of it optional).
They use jupyter notebooks and have adapted to present solutions in
scikit-learn apart from the proprietary stuff they initially started off
with because one of the instructors was a founder of an AI and ML start-up
that they tried promoting  ( Maybe you've heard of Dato, now goes by the
name of Turi - acquired by Apple).

It should give you a good, firm grasp on the basics and enough to keep you
busy for a while.

On Wed, Jun 7, 2017 at 7:41 PM, Anand Chitipothu <anandology at gmail.com>
wrote:

> On Tue, Jun 6, 2017 at 8:59 PM, Ramkrishna P <ramkrishna001 at gmail.com>
> wrote:
>
> > Hello Team,
> > I have started out to work on pandas and numpy libraries to pick some
> > machine learning concepts.
> > I feel apart from working on datasets and getting some results, the
> > core concepts of machine learning are still missing.
> >
> > If you guys could suggest some resources, it will be of great help.
> >
>
> I find Learn Data Science very good place to start, esp. for the beginners.
>
> http://learnds.com/
>
> Anand
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-- 
Arjunil Pathak