The Open in colab button for viewing Python Notebooks in Google Colab, has had some issues in recent months, so if it does not work, please download the raw file and view in an IDE like Jupyter Lab or VSCode to see and interact with the full project.
A curated collection of hands-on Machine Learning and Deep Learning mini-projects, experiments, and pipelines — developed using real-world datasets, modern libraries, and academic theory in action.
📍 Ongoing portfolio by Aaron Howell – AI Engineer Intern @ Live Digital, MSc in AI @ UWE Bristol, 2x Scholar 💡
📧 Email Me: [email protected]
This repository contains Jupyter notebooks and visual artefacts from end-to-end ML projects. Topics range from image classification to efficient data loading in PyTorch, including:
- ✨ Multimodal I/O with Gemini Developer API LLMs, LMMs (ft. Diffusion)
- 💬 Simple ReAct LLM, GPT Agent From Scratch using OpenAI API
- 📋 Transcribing Text Documents with Claude 4 Opus API
Each notebook is designed to be:
- Reproducible ✅
- Educational 🧠
- Scalable 🔄
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ML/AI Topics
- Agentive Systems
- AI Engineering
- Designing Machine Learning Systems
- Machine Learning Algorithms
- Deep Learning Algorithms/Architectures (CNNs, Transformers, RNNs .etc)
- Generative AI
- Natural Language Processing
- Computer Vision
- Supervised Learning (Regression, Classification)
- Efficient Data Pipelines
- Performance Benchmarking & Optimisation with CUDA (CPU vs GPU)
- Exploratory Data Analysis (EDA)
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Languages & Libraries
- Python
- R
- PyTorch
- Scikit-Learn
- Pandas
- NumPy
- Matplotlib
- Seaborn
-
DevOps Practices
- Git, GitHub
- Configuration Management
- YAML
- JSON
- JSONPath
- APIs
-
Cloud Skills
- Amazon AWS
- Microsoft Azure
- Google Cloud Platform
-
Mathematics for ML
- Linear Algebra
- Probability & Statistics
- Integral Calculus
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📸 Visual Explanations of Theory in "machine learning concepts"
This repo also includes diagrams and annotated images that break down concepts such as:
- Data loading & processing
- Model pipelines
- Tensor ranks and operations
This portfolio is Work In Progress (WIP) — I actively update this repo with:
- New notebooks 📒
- Visual insights 📊
- Real-world end-to-end projects with Kaggle Datasets 🔍
After reading the UK National AI Strategy in 2022, I predicted a rapid shift in the global workforce economy and began my journey into STEM and Artificial Intelligence, culminating in a 1st Class Degree in Automotive and Transport Design from Coventry University with a STEM-flavoured itch to scratch at Postgraduate level.
As I mentioned briefly above, I read the UK's National AI Strategy in 2022, which informed me of the government's plan to scale-up and commit massive investment and sponsorship of AI through UKRI and Innovate UK, and decided that I was ready to embark on a journey to STEM, but that's not all. Before that, I:
- Read Life 3.0 by Max Tegmark twice between 2018-19, and was instantly hooked
- Designed several Autonomous Cars for the year 2030, and learned about LiDAR and Computer Vision for Autonomous Driving to better inform design philosophy
- Most cars that my classmates and I were tasked with designing were to use SAE Level 5 Technology (Fully Autonomous Driving)
- In October 2022, I was invited to compete in the Sir William Lyons Award at the Royal College of Art, London, as a Finalist with 3 other contestants, with £2.5k to be won each.
- By this time, I had already read Max Tegmark's book and had decided that for my presentation to the judge panel, including a former design director at Rolls-Royce and the London Lord Mayor, I would offer a dedicated section off-script to discuss the future of Artificial Intelligence.
- For this section, I showed the panellists a screenshot of a YouTube channel that my design mentor and I had created with a GenAI video we had created together that to this day has amassed 2.1 million views (and is monetised), using a fine-tuned Stable Diffusion model and Midjourney along with some animation tools.
- This video that we made was pre-video-generation days, so it went viral due to being considered State of the Art
- The panellists were so impressed with the foresight to include a discussion about AI that all my post-presentation Q&A was spent having a discussion about it, probing my opinions about the future of work in the Automotive industry in the dawn of generative workflows.
- When the awards were presented, every contestant except me was awarded £2.5k, with one being awarded £5k instead of me getting a share, as had happened in previous competition years.
- This is because it was explained to me afterwards that they felt that the other contestants would use the money better for a career in automotive design specifically, whereas they could see that I was heading in a different direction.
- The London Lord Mayor said, "You would have won an award in the future, but your presentation was 5 years too advanced"
- Another panellist said, "I don't know what it is you will go on to do, but you're going to do great things"
- While I had partially felt like I had missed lectures to travel to London for a disappointing end, I took home those 2 aforementioned encouragements that I will remember for the rest of my life, along with a burning determination to change my future before it changed around me.
- I'm currently an AI Engineer Intern @ Live Digital, a SaaS Recruitment Agency, seeking to automate their processes with an AI-powered client acquisition engine, using a GenAI pipeline, as I am on a gap year to gain industry experience.
- I resume studying in September 2026 (completing in May 2027)
I have also recently been awarded 2x Scholarships and a Youth Development Award from the King's Trust.
- O'Reilly DEI Data Science Scholarship (2025-2026 Winner)
- MyWorld Scholarship (2024-2025 Winner)
- Youth Development Award (2024 Winner)
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🧠 Applied AI & ML
- Designing Machine Learning Systems
- AI Engineering
- Machine Learning Engineering
- MLOps
-
🏭 Real-time industry integration
-
📊 Data-driven decision systems
- Image Classification CNNs (Computer Vision), with MNIST Handwritten Digits in PyTorch
- 2020-2025 AI Job Salaries Prediction, Kaggle Dataset, ANN Regression in PyTorch
- Deep Learning in PyTorch with Python Bootcamp, Pierian Training, Udemy
- Software Engineering Practices, Udemy
- Research Methodology, Udemy
- Optimisation with Python, Udemy
- Computer Hardware, OS, Networking, Udemy
- Complete SQL Bootcamp, Udemy
- DevOps, Configuration Management: YAML, JSON, JSONPath
- Introduction to Cloud Computing in AWS, GCP, Azure
- Master Git and GitHub
- Master Math (Linear Algebra, Integral Calculus, Probability & Statistics) in Python
- 🔗 LinkedIn Profile
- 📁 Kaggle
- ✨ Featured on UWE
- 📧 Email Me: [email protected]