February 9, 2020

442 words 3 mins read



Course notes for Data Science related topics, prepared in LaTeX

repo name yogeshhk/TeachingDataScience
repo link https://github.com/yogeshhk/TeachingDataScience
language Jupyter Notebook
size (curr.) 675595 kB
stars (curr.) 36
created 2019-04-13
license GNU General Public License v2.0

Teaching Data Science

LaTeX course notes for Python, Machine Learning, Deep Learning, Natural Language Processing, etc. Core content is in the form for Beamer slides, which in turn can get compiled into presentation mode as well as two-column course notes mode.

All tex sources and images have been open sourced as I have taken from others, learnt from others, although I have added some of mine, I need to give it back!! LinkedIn post: https://www.linkedin.com/feed/update/urn:li:activity:6523000857385103360

Copyright (C) 2019 Yogesh H Kulkarni


  • LaTeX (tested with MikTex 2.9 on Windows 7, 64bit)
  • Need to install LaTeX packages, as and when you get such warning/suggestions.
  • Using TexWorks as IDE

Code Arrangement

  • LaTeX directory
    • Has tex sources along with necessary images
    • Naming: subject_maintopic_subtopic.tex eg maths_linearalgebra_matrices.tex
    • Main_Workshop/Seminar_Presentation/CourseMaterial.tex are the driver files
    • They intern contain common content files, which have included actual source files
    • Make bat files compile the appropriate sources
  • Code directory
    • Has running python or ipython notebook files with necessary images and data
    • Naming should be such that corresponding latex file can be associated
    • Library based tex file, say, sklearn_decisiontree.tex will have just template code and short fully working examples from Mastering Machine Learning whereas the sklearn_decisiontree.ipynb will have running workflows. No need to sync both. You may want to keep ipynb’s pdf in LaTeX/images directory for reference
  • References directory (not uploaded, as it is mostly from others github repos, nothing much of mine)
    • Has papers, code, ppts as base material to be used for content preparation

How to Run:

  • Driver files for the courses are named with “Main_Workshop/Seminar__CheatSheet/Presentation.tex”
  • Both the Cheatsheet (meaning course notes in two column format) and Presentation.tex refer to same core content file, which in turn contains are the topic files.
  • Run make bat for the course you need. Inside, its just a texify command, so you can modify it as per your OS.
  • You can compile individual “Main_Workshop/Seminar__CheatSheet/Presentation.tex” also using your LaTeX system.
  • Instead of these given driver files, you can have your own main files and include just the *content.tex files.


  • Author (yogeshkulkarni@yahoo.com) gives no guarantee of the correctness of the content. Notes have been built using lots of publicly available material.
  • Although care has been taken to cite the original sources as much as possible, but there could be some missing ones. Do point them and I will update wherever possible.
  • Lots of improvements are still to be made. So, don’t depend on it at all, fully.
  • Do send in your suggestions/comments/corrections/Pull-requests.
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