Instructor: Marco Morales, Columbia University
TAs: Rachel Lee, Columbia University
Heinrich Peters, Columbia University
This repository is a companion to the course Projects in Advanced Machine Learning taught at the Quantitative Methods in the Social Sciences program over the Spring of 2022. It contains curated reference materials, slides and sample code. You can find the most updated version of the course syllabus here. Make sure to check regularly for updates.
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Textbooks: While there are no required textbooks for this course, you will find these books to be very useful in addition to the lectures and course readings:
- François Chollet. Deep Learning with Python. Manning Publications. Greenwich CT, 2017
- Andreas C Müller and Sara Guido. Introduction to Machine Learning with Python. O’Reilly Media, Boston, MA, 2016 [e-version available through Columbia Libraries]
- Aurélien Géron. Hands-On Machine Learning with Scikit-Learn and TensorFlow. O’Reilly Media, Boston, MA, 2017 [e-version available through Columbia Libraries]
- Max Kuhn & Kjell Johnson. Applied Predictive Modeling. Springer, New York, NY, 2013 [e-version available through Columbia Libraries]
- Trevor Hastie, Robert Tibshirani & Jerome Friedman. The Elements of Statistical Learning. Springer, New York, NY, 2009 [e-version available through Trevor Hastie's site]
- Ian Goodfellow, Joshua Bangio & Aaron Courvill. Deep Learning. MIT Press, Cambridge, MA, 2016 [e-version available through Columbia Libraries]
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Cloud Services: The course will work in the cloud, and rely heavily on Colaboratory and AI Model Share; registered students will receive instructions on access to these services. Sign up for a GitHub account if you don't already have one.
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install git in your local machine
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from the command line, go to the directory where you want to clone this repo
$ cd <your chosen directory>
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clone
this repository to get a local copy in your machine$ git clone https://github.com/marco-morales/QMSS-GR5074_Spring2022.git
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pull
every week before class to sync your local copy with the lates changes pushed to the repo$ git pull origin main
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"Watch" the repository to get notifications each time uptates are pushed
Acknowledgements: Materials in this repository derive from previous iterations of this course taught by Mike Parrot.