Collaborative Filtering
Collaborative filtering is a general solution to the following problem: given behavioural features for items, what are the underlying factors that describe or connect them. This sounds very vague, but think of it this way: Netflix uses collaborative filtering to understand the preferences (underlying factors) that its users (items) have, so that it can make…
Classifying Pet Breeds and Fine-Tuning a Neural Net
This post follows fastai’s content on building, training and fine-tuning Neural Networks. It leverages one of the examples provided in their course involving classifying the breeds of dogs and cats. The code for this example is stored on my GitHub. Connecting to the data and pre-sizing the images I connected to fastai’s PETS dataset, and…
Implementing k Nearest Neighbours from scratch in Python
This post is a follow up from the previous post. I will work through an implementation from scratch in python. The code is saved at my github. The data The data is a well known dataset related to features of Iris flowers, from the Iris Plants Database. It might be the best known dataset in…
Algorithm Overview: k-Nearest Neighbours
k-Nearest Neighbours (k-NN) is a non-parametric classification algorithm that has been around since the 50’s. It is typically used for classification, but can also be used for evaluation. With classification, a data point is compared to the k observations closest to it, and the classes of those observations infer the class of the data point.…
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