This repository stores the MLCC Laboratories for the MLCC (Machine Learning Crash Course) summer school http://lcsl.mit.edu/#/courses.
This version implements the code in python. Please see another repository for the Matlab implementation.
The labs are based on prior source code available that was develop for the MLCC summer school prior to 2019. This repository is a consequence of all this prior work and is an effort to clean up and centralize the content. Many of the files used here are based on the work done at MLCC 2018, at https://github.com/mzanetti79/MLCC18.
Each laboratory contains a solution file. Please do not jump to that immediately but rather use it as a resource when you are stuck.
All source code was tested with the following setup:
- python 2.7
- numpy 1.16.4
- matplotlib 2.2.4
- scipy 1.2.2
- PyCharm IDE.
You can download the code locally, but you can also use git. If you are new to using Github please check:
- https://www.tutorialspoint.com/git/
- Traversy Media's "Git & GitHub Crash Course For Beginners" available here.
If you are new to python then please check the following resources:
- https://docs.python.org/2/tutorial/
- https://www.learnpython.org/
- Mosh' "Python Tutorial for Beginners [Full Course] 2019" available here.
If you are unable to install python and all dependencies on your system then please consider using an online system (like https://jupyter.org/try) and look at the MLCC 2018 resources https://github.com/mzanetti79/MLCC18.
Each laboratory has a pdf to guide you through the work. Start there and good luck!
June 2019, C. Rusu