Yello Hello! My name is Chi, and this is my third set of posts on this blog. In my last post, I looked at machine learning models that could differentiate between genres of music. If you’ve read any of my previous posts, you would’ve already had the understanding that I have no understanding of data […]
Read More Edmonton Property Assessment #1 – IntroI’m extremely happy with how gradient boosting turned out in my last post. I think I’ve just had xgboost on the brain… since it’s worked so well in my last 2 projects. KNN should’ve been the first thing that came to my head when I thought about this haha. I don’t think I’ve actually done […]
Read More Edmonton Property Assessment #5 – Building A Regression Model (K-NN)Okay, so I’ve gotten to explore the data set a little bit, statistically and spatially. I now want to built a model. With the model, I’m not necessarily trying to predict anything, but I almost want to use regression as a means for data exploration and data visualization as well. In the ideal world, I’d […]
Read More Edmonton Property Assessment #4 – Building A Regression Model (Gradient Boosting)In the last post, I looked at the most valued neighbourhoods in the city by average assessed value. We were coming across neighbourhoods like “Uplands”, “Decoteau”, and “Aster”… where are these neighbourhoods? I have no clue to be honest. I can’t even say I’ve heard of these neighbourhoods or anything resembling their names. “Decoteau”? I […]
Read More Edmonton Property Assessment #3 – Geographical MappingGetting the Data Getting the data was quite simple. The Edmonton Open Data portal has a Property Assessment page. I’ve downloaded the dataset into the data folder of this project. Loading the Data Let’s fire it up into pandas and check out a few data points! In [1]: # Enable plots in the notebook %matplotlib inline […]
Read More Edmonton Property Assessment #2 – Exploring Property Assessment Dataset
