Practical research and working code
Practical AI, quantum computing and optimisation
Clear, reproducible guides covering Qiskit, developer workflows, algorithms, simulation and practical computing.
Explore the work
AI & developer workflows
Applied notes on AI tools, local models, automation and reliable publishing workflows.
Quantum computing
Qubits, gates and algorithms explained with diagrams and executable Qiskit examples.
Algorithms & optimisation
Heuristics, modelling and simulation methods presented through practical experiments.
Practical computing
Concise guides for macOS, Homebrew, hardware and everyday technical work.
Featured guides
Quantum learning path
Quantum Computing: A Complete Learning Path
A structured route from qubits and gates to circuits, algorithms and Qiskit experiments.
AI workflow
Publish to WordPress with Claude and MCP
A practical workflow for drafting, publishing and troubleshooting WordPress content.
Optimisation
Solving the Traveling Salesman Problem
Nearest neighbor, 2-opt, 3-opt and tabu search explained as a practical progression.
Latest writing
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Pocket Data Science VIII: Kaggle Store Sales Quad-Ensemble
Why a 2.6x back-to-school multiplier and a 52-week lag both hurt our RMSLE, why leaf-wise LightGBM beat CatBoost, and how…
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Pocket Data Science VII: Store Sales Gradient Boosting on Android Termux
Ridge, CatBoost, and a hybrid residual ensemble for Kaggle Store Sales in Android Termux, reaching 0.41072 RMSLE and rank #116.
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Pocket Data Science VI: Store Sales Time Series Baselines on Android Termux
Five non-ML baselines for Kaggle Store Sales, built in Android Termux. Follow the heuristic ladder from 4.37970 to 0.43150 RMSLE…
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Pocket Data Science V: Kaggle NLP on Android Guide
Yes, train NLP transformers on Android. Sloppy subword tokenization causes vocabulary out-of-bounds errors on Kaggle. See our 5-model ensemble guide…
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Superdense Coding Explained: 2 Bits in 1 Qubit Qiskit Guide
Yes, 1 qubit sends 2 bits with shared entanglement. Without it, the Holevo bound caps one qubit at 1 classical…
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Pocket Data Science IV: Kaggle MNIST Subspace SVM Guide
Yes, run MNIST SVMs on mobile. Training full 784-D kernels on phone exhausts RAM and crashes Termux. See the 50-D…
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