We reside in an era of superlatives. Annually, month, week, latest advancements in machine learning research are announced. The variety of (ML) papers added to arXiv is growing equally fast. Greater than 11 000 papers have been added last October within the Computer Science Category.
Similarly, large machine learning conferences are seeing ever-growing variety of submissions — so many the truth is, that, to make sure a good reviewing process, submitting authors are required to function reviewers for other submissions (called reciprocal reviewing).
Each paper possibly introduces latest research results, a brand new method, latest datasets or benchmarks. As a beginner in Machine Learning, it’s difficult to even start: the quantity of data is overwhelming. In a previous article, I argued that and why ML beginners should read papers. The quintessence is that good research papers are self-contained lectures that hone analytical considering.
In this text, I give beginners ideas on how and where to search out interesting papers to read, some extent that I didn’t fully elaborate previously. Over 7 steps, I guide you thru the possible technique of finding and reading interesting papers.
