I am an Irish data scientist, and this is a place where I post projects and notes.
My Latest Posts
- Collaborative FilteringCollaborative 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 makeContinue reading “Collaborative Filtering”
- Classifying Pet Breeds and Fine-Tuning a Neural NetThis 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, andContinue reading “Classifying Pet Breeds and Fine-Tuning a Neural Net”
- 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 inContinue reading “Implementing k Nearest Neighbours from scratch in Python” - Algorithm Overview: k-Nearest Neighboursk-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.Continue reading “Algorithm Overview: k-Nearest Neighbours”
- Cross Entropy Loss
In a previous blog post I described the process of training a neural network for classifying the quality of Guinness. That was a binary classification problem (the result was ‘good’ or ‘bad’) and a key step in it was using the sigmoid function to ensure that the model’s activations were between 0 and 1. ThisContinue reading “Cross Entropy Loss” - Redundant Encoding in Data Visualisations
Redundant Encoding is the practice of adding multiple visual elements to a visualisation, to enhance effectiveness and ease-of-understanding. It is also referred to as redundancy. According to displayr.com, it can ‘improve the chances of a reader interpreting a visualization quickly and correctly’. Redundant encoding applies to many elements of a visualisation, including colours, shapes, labels,Continue reading “Redundant Encoding in Data Visualisations” - Building a Neural Network from scratch using PyTorch and FastAI
This post follows content from fastai to build a two layer Neural Network from scratch using python. The code is saved on my github. The data, and data prep I used a sample dataset from FastAI based on a famous computer vision dataset, MNIST. The sample dataset uses 3s and 7s only, to make theContinue reading “Building a Neural Network from scratch using PyTorch and FastAI” - A Simple Demonstration of Gradient Descent in Python
This post looks at the concept of gradient descent, and applies it to a simple function. It is prompted by and takes some code from the fastai lesson content.Put simply, gradient descent is used to give feedback to a deep learning model so it can adjust its parameters. The intention is to prompt the modelContinue reading “A Simple Demonstration of Gradient Descent in Python” - Deploying a Python Neural Net using Binder
The previous blog post trained a neural network to classify images of Guinness. This post will demonstrate how to host the model on Binder so that people can use it themselves. What is Binder? The Binder Project helps you create one-click, sharable, live code environments from public code repositories that runs entirely in the cloud.Continue reading “Deploying a Python Neural Net using Binder” - Guinness Image Classifier: Training the model in Python using fastai
I have been learning about Neural Networks and Image Classifiers through fastai recently, and wanted to try apply what I had learned to a problem outside the scope of that material. The Problem Any Irish person that drinks Guinness will probably have strong opinions on the quality of the drink in just about any pubContinue reading “Guinness Image Classifier: Training the model in Python using fastai”
