Re: [BangPypers] Resource for ML

2017-06-07 Thread 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

Re: [BangPypers] Resource for ML

2017-06-07 Thread Anand Chitipothu
On Tue, Jun 6, 2017 at 8:59 PM, Ramkrishna P 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. > > I

Re: [BangPypers] Query regarding packages in PyPI.

2017-06-07 Thread Harsh Gupta
If you are want download a lot of packages and can't do pip install, you can try creating a local mirror of PyPI. You can use the following tools for that: * Bandersnatch https://bitbucket.org/pypa/bandersnatch * DevPi http://doc.devpi.net/latest/ On 7 June 2017 at 18:53, Rajvi Dhimar wrote: >

Re: [BangPypers] Resource for ML

2017-06-07 Thread Propadovic Nenad
Hello, while not having finished Andrew Ng's coursera course (yet), I started it and like it, too. I don't think it's an disadvantage that it's Matlab (or it's open source counterpart, Octave) - based (and I'm much more proficient in Python than in Matlab). Thanks to Abhinav and Harsh for the other

[BangPypers] Query regarding packages in PyPI.

2017-06-07 Thread Rajvi Dhimar
Hello experts, I am trying to get certain packages from pypi onto a network device. On the device I cannot do a 'pip install'. I need to write a shell scripy to fetch the package (using curl or fetch command) from PyPI on to my network device. Earlier, the packages were located at https://pypi.py

Re: [BangPypers] Resource for ML

2017-06-07 Thread Harsh Gupta
I collected some ML resources for inter hostel data analytic competition here https://github.com/Azad-Hall/data-analytics Other the Andrew ng's course, Caltech's "Learning from Data" ( http://work.caltech.edu/telecourse.html) course is really good for the theoretical foundations of ML> On 6 June

Re: [BangPypers] Resource for ML

2017-06-07 Thread Abhinav Upadhyay
On Tue, Jun 6, 2017 at 8:59 PM, Ramkrishna P 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