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How to Read Machine Learning Papers Effectively

Youssef Hosni
Towards AI
Published in
10 min readOct 9, 2022

The field of machine and deep learning is evolving very fast, and there are new research outputs every day. Therefore you will need to read papers to stay updated with the new algorithms and techniques in this field. Reading a research paper is very important as it increases your knowledge and gives you a deeper understanding of a certain topic and is a key element to staying at the top of your field, especially if you are working as a researcher. Andrew NG says:

If you read 5 -20 papers in a certain topic such as object detection you will have a basic understanding of it, while if you read 50 -100 papers and understand most of them you will have a very good understanding of an area or you might even master it.

Therefore every machine learning researcher or practitioner needs to develop a habit of reading a research paper and be able to do it effectively. In this article, I will go through how to effectively and efficiently read a research paper without losing interest or putting too much time and effort without any benefits.

Photo by Annie Spratt on Unsplash

Table of Contents:

  1. Why You Read a Research Paper
  2. Exploring a Research Paper
  3. Increase Your Knowledge
  4. Applying
  5. Building Upon

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Written by Youssef Hosni

Data Scientist & AI Researcher | Subscribe to my Newsletter: https://youssefh.substack.com/ | E-Books & Courses: https://youssefhosni.gumroad.com/

Responses (18)

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Interesting read! Thanks for sharing your framework for reading scientific papers. I like the idea of deciding if the paper is worth a full read or not.

Nothing about critical assessment? Of questioning premises and assumptions?

Just a few grammar suggestions (I have OCD):
Model Architecture: Almost every paper will have an architecture diagram. Understanding this will help *you* to have a better understanding of...
Inputs & Outputs: Understanding the inputs and the outputs…