Papers

Collection of my reading notes, reference to summary of ML papers I've read Inspired by [Denny Britz] and [Daniel Seita].

Reading Guide

Questions to guide through reading (Reference: Guide to Reading Academic Research Papers)

1. What previous research and ideas were cited that this paper is building off of? (often in the introduction)
2. Was there reasoning for performing this research, if so what was it? (introduction)
3. Clearly list out the objectives of the study
4. Was any equipment/software used? (methods)
5. What variables were measured during experimentation? (methods)
6. Were any statistical tests used? What were their results? (methods/results)
7. What are the main findings? (results)
8. How do these results fit into the context of other research and their 'field'? (discussion)
9. Explain each figure and discuss their significance.
10. Can the results be reproduced and is there any code available?
11. Name the authors, year, and title of the paper!
12. Are any of the authors familiar, do you know their previous work?
13. What key terms and concepts do I not know and need to look up in a dictionary, textbook, or ask someone?
14. What are your thoughts on the results? Do they seem valid?

Workflow

1. copy name of paper
2. use pnote <paper name> to open new note doc for editing
3. new note doc is in daily/ by default, organize them to database at the end of the day

How to use Notion for paper reading

• use flask to make the interface

• use notion-py to connect with Notion database

• use zotero-py to connect with Zotero data

• use mendeley to connect with Mendeley data

• to get all pages, use https://github.com/eoranged/notion-scripts/blob/master/audit.py