- I am going through the Deep Learning Specialization. I have finished the first two courses and will finish the rest as well.
- I am proficient in coding.
- I am familiar w/ the basics of calculus, linear algebra and probability having done electrical engineering courses in college and computer science courses in grad school.
- I am taking courses in the Math for ML and Data Science Specialization to refresh my math concepts. I have finished the first two courses (though they seemed way too basic).
As I am doing these courses, I wanted to get in the habit of reading 1-2 research papers every week. However, I do not want to start w/ papers that are way too specialized or deal w/ a narrow field or are experimental or have advanced math or a poorly written for the general audience.
I prefer well-written seminal/foundational/mainstream/popular papers (even if they are old) that deal w/ the general concepts and the most popular/well-established algorithms. I prefer papers with some math and that have links to any code/notebooks.
PLEASE can you recommend me a reading list. A list of 10 papers should suffice. I will REALLY appreciate it!