From the archive
Machine Learning
Practical machine learning implementations, algorithms, and real-world applications
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QLoRA on a Single GPU: Does a 7B Model Fit in 8GB?
Use a tested Python memory calculator to separate four-bit weights from QLoRA training memory, and measure the parts an 8GB claim leaves out.
Includes verification notes - ↗
Build RAG From Scratch in Python: Test Retrieval With LangChain
Build a tested LangChain retrieval-to-prompt pipeline with source IDs, access scopes and repeatable indexing, before adding model generation.
Includes verification notes - ↗
Predicting Exam Outcomes in Ruby: Split Before You Scale
Use Rumale to fit preprocessing on training rows only, evaluate a synthetic exam-outcome fixture and inspect threshold errors against a baseline.
Includes verification notes - ↗
Implementing the Rasch Model in Python: Fix the Scale Before Fitting
Build and test a penalized Rasch estimator in Python, with a zero-mean difficulty constraint, checked gradients and extreme response cases.
Includes verification notes - ↗
Build a Bayesian text classifier in Ruby, then check the arithmetic
Implement multinomial Naive Bayes with word counts, smoothing and log scores. Test unknown words, empty input and a small held-out fixture.
Includes verification notes - ↗
Machine Learning in Ruby: Train, Check and Reload a Ruby-FANN Network
Train an actual Ruby-FANN XOR network, validate inputs and reload saved weights using a documented Ruby 3.3 compatibility build.
Includes verification notes - ↗
Healthcare ML: a perfect score can be a broken split
A reproducible Python example shows patient leakage turning memorization into perfect accuracy, then checks how prevalence changes positive predictions.
Includes verification notes