We live in an era of superlatives. Every year, month, week, new advances in machine learning research are announced. The number of articles (ML) added to arXiv is growing equally fast. More than 11,000 articles have been published. added last October in the Computer Science Category.
Similarly, large machine learning conferences are seeing increasing numbers of submissions; in fact, so many that, to ensure a fair review process, authors must act as reviewers for other submissions (called mutual review).
Each article may present new research results, a new method, new data sets, or benchmarks. As a beginner in Machine Learning, it's hard to even get started: the amount of information is overwhelming. In a previous article, I discussed that and why ML beginners should read articles. The quintessence is that good research papers are stand-alone lectures that hone analytical thinking.
In this article, I give beginners ideas on how and where to find interesting articles to read, a point I didn't fully make above. Over 7 steps, I guide you through the potential process of finding and reading interesting articles.
