For the past few weeks, I tried to build a board game recommmender as my side project; However, I failed to beat the baseline model. Due to time limits, I had to abort this project and move on to other stuff. Netherlevess, I feel that my failure may help those who are new to recommendation system, and that is the purpose of this blog post. I will explain some techniques I (mis)used, and problems that might cause the undesirable performance.
Recently, I worked on a side project which allows me to perform sentiment classification in Chinese text. The program can classify any given sentence as either positive or negative.
My motivation of writing this very first blog at the last day of 2018 came from a casual conversation between me and my boyfriend. He said he would look back what he achieved for the last 12 months and felt proud, which reminded me of a Chinese meme