Skip to content

An introductory course to machine learning

Notifications You must be signed in to change notification settings

bml13052000/IO_Course

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

22 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Implementation part of the Summer IO course

the code is divided into weeks, with jupyter notebooks in each of those directories.

Install anaconda and jupyter notebook. You should have scikit-learn, numpy, pandas and Tensorflow (if not Tensorflow, then PyTorch) installed.

Week 4 onward, there are implementations of neural networks in Tensorflow. However, I encourage you to look at Pytorch if you're interested as well. I will provide links to detailed explanation and implementation in Pytorch at the end of every TensorFlow implementation.

If you are stuck with anything related to neural networks at any point (not just the implementation but the concept itself), then read the PyTorch documentation on that topic. This is the link to the docs. A simple google search of the format <concept_name> :pytorch in the search bar will get you the pytorch docs as the first result. I recommend reading them as they are extremely well written.

About

An introductory course to machine learning

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 100.0%