Posts

Word-For-Word Translator

With the help of Google Translater, Deepl, and LLMs such as ChatGPT, translating text from one language to another has never been easier. However, this doesn’t necessarily help you learn it. For example, I’m intermediate-level Korean. I can read most Korean, but there is the odd word I don’t know. Putting the sentence into a translator often doesn’t help as, due to sentence structure, idioms, meaning etc, it can be difficult to tie the output back to the input. The best solution is to put the unknown word into a dictionary or translator, but that’s time-consuming.

Friday, October 10, 2025 | 1 minute Read

Visualising Decision Trees, Random Forests, Gradient Boosted Trees

I wrote a series of posts for Towards Data Science concerning visualising the various types of trees and using this to tune hyperparameters. Read the full series here: A Visual Guide to Tuning Decision-Tree Hyperparameters A Visual Guide to Tuning Random Forest Hyperparameters A Visual Guide to Tuning Gradient Boosted Tree Hyperparameters

Tuesday, October 7, 2025 | 1 minute Read

UK House Prices Map

I built an interactive map for UK house prices. You can see things such as: What was the median property price in W1 in 2015? Where is the median price for a flat under £300,000? Where can I afford a detached house on 15x salary? How have office prices changed over time? It’s a bit slow as it’s hosted on a minimal GCP Cloud Run instance to save costs, and there is a lot of data. If it crashes, just refresh.

Friday, September 19, 2025 | 1 minute Read

Achievements and Certifications

137 and counting! Covering data science, cyber security, IT, and more. Warning: this page has a lot of images so may take a while to load. Consulting Data Science Kaggle 365 Data Science

Wednesday, August 20, 2025 | 1 minute Read

Kaggle: Predict the Introverts from the Extroverts

I’ve spent the last few months (and continue to spend them) working for an EV startup - as such, I’ve had a lot less time for personal projects such as this. The Kaggle notebook for this project can be found here: https://www.kaggle.com/code/jamesdeluk/ieclassifier It’s a quick and dirty one, not particularly tidy - I just felt the urge to have a play. Don’t judge me. Intro A simple challenge from Kaggle’s Playground series, called Predict the Introverts from the Extroverts. It can be found here: https://www.kaggle.com/competitions/playground-series-s5e7

Friday, July 25, 2025 | 7 minutes Read

Basic APIs: Diamond Pricing with FastAPI, Docker, GitHub Actions, and Azure

This has been a long time coming! Basic APIs part one was posted back in January; since then I’ve started a new job and have had some contract/freelance work, so I didn’t get around to completing this. Also, since then, I’ve moved from Windows to Mac, and started using uv instead of pyenv/pip, so things may look a little different. The repo for this project can be found here: https://github.com/jamesdeluk/data-projects/tree/main/basic-apis/diamond-price The goal Send (POST) to an online API with diamond criteria, and get a predicted price as a response.

Thursday, March 6, 2025 | 12 minutes Read

Financial Intelligence - Karen Berman & Joe Knight

Excellent book. Finance underpins everything, and this explains everything in an approachable, mostly non-technical way. There are a bunch of notes below, but it’s only scratching the surface of what the book includes. Anyone in any position in any organisation would benefit from a read, and it’s one I’ll be re-reading. General finance concepts The art of accounting and finance is the art of using limited data to come as close as possible to an accurate description of how well a company is performing.

Sunday, February 2, 2025 | 18 minutes Read

Bonus: DVLA Data Dashboard in Power BI

This project follows on from my one on analysing DVLA data. If you haven’t already read it, you may want to do so - you can find it here: https://www.jamesgibbins.com/analysing-dvla-data/ Intro Time for something different - a dashboard! Sure, Python is great for transforming and analysing data, but it’s not the most end-user-friendly†. This is why business intelligence (BI) / data visualisation tools exist, the most popular of which is Microsoft’s Power BI.

Saturday, January 18, 2025 | 7 minutes Read

Analysing DVLA Data for Vintage Comebacks

GitHub repo: https://github.com/jamesdeluk/data-projects/tree/main/dvla-vehicle-statistics Intro The DVLA website provides vehicle licensing data, updated every few months. As a car and data enthusiast, I wanted to have a poke around. I started with two primary questions: What are the most popular vehicles in the UK? Which old vehicles are having a comeback? → This might suggest they will appreciate in value! Selecting the dataset There are a few different datasets, available here: https://www.gov.uk/government/statistical-data-sets/vehicle-licensing-statistics-data-files The one(s) I decided to use were:

Data Analysis

Friday, January 17, 2025 | 21 minutes Read

Basic APIs: Sentiment Analysis with Flask, Docker, and AWS

The repo for this project can be found here: https://github.com/jamesdeluk/data-projects/tree/main/basic-apis/sentiment-analysis The goal Send (POST) a word or phrase to an online API, and get a sentiment (positive or negative) and score as a response. Step 1: Build the Python script First we need the script that can take a word or phrase as an input and return a sentiment. import json from textblob import TextBlob def analyse(data): text = data.get('text', '') if not text: return json.dumps({'error': 'No text provided'}), 400 blob = TextBlob(text) sentiment_score = blob.sentiment.polarity return json.dumps({ 'input': text, 'sentiment_score': sentiment_score, 'sentiment': ( 'positive' if sentiment_score > 0 else 'negative' if sentiment_score < 0 else 'neutral' ) }) The API will be JSON-based, so this script is also. The function takes some text and uses TextBlob to give it a sentiment score between 1 (positive) and -1 (negative), which it returns, also in JSON form.

Wednesday, January 8, 2025 | 7 minutes Read

Top Media of 2024

A quick round-up of the movies I watched, books I read, podcasts I listened to, and YouTube videos I liked, in the past year. Movies Top 3 in bold, prioritising new releases The Time Traveler’s Wife Final Destination 3 Paul American Fiction Warrior Alien³ Sisu The Fall Guy The Beekeeper Furiosa: A Mad Max Saga Bad Boys: Ride or Die Bill & Ted’s Excellent Adventure Inside Out 2 Kung Fu Panda 4 Dune: Part Two Sleep Poor Things The Worst Person in the World The Life and Death of Colonel Blimp Up Black Hawk Down Deadpool & Wolverine Elite Squad The Batman The Ministry of Ungentlemanly Warfare Godzilla Minus One Prometheus Alien: Romulus Bill Bailey’s Jungle Hero Hot Fuzz Shaun of the Dead Exhuma The Substance Men in Black Gladiator Gladiator II 500 Days of Summer Casino Royale Skyfall GoldenEye Wallace & Gromit: Vengeance Most Fowl Books Fiction Top 3 in bold

Saturday, January 4, 2025 | 6 minutes Read

Podcast Sentiment and Topic Analysis

Intro I am a bit of a podcast addict. One of the podcasts I listen to most, The Jordan Harbinger Show, has Feedback Friday every week. It’s effectively an agony aunt, except with two uncles. I always loved it, but over time I’ve felt it has become too negative - too many stories about addiction and abusive relationships. They’re interesting to discuss, but they’re a bit depressing. I wanted to test this hypothesis. Jordan is nice enough to provide all the transcripts on his website, so I thought I’d analyse the FBF episodes from the last year and see if they really are negative. While I had the data, I thought it would be interesting to extract common themes and topics too.

Thursday, January 2, 2025 | 11 minutes Read