📚 Curated collection of engineering blogs detailing real-world applications of LLMs in solving specific business problems.
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Updated
Sep 13, 2025
📚 Curated collection of engineering blogs detailing real-world applications of LLMs in solving specific business problems.
📚 Curated list of machine learning engineering blogs.
Catches music sold as lossless that was secretly compressed. It accuses only when independent lines of evidence agree, because a false accusation costs more than a miss.
📚 Curated collection of blogs and papers on how different companies are using machine learning in production for better customer support.
This article explores the theory behind explainable car pricing using value decomposition, showing how machine learning models can break a predicted price into intuitive components such as brand premium, age depreciation, mileage influence, condition effects, and transmission or fuel-type adjustments.
Advanced sentiment analysis lab with TF-IDF word/char features, leakage-safe multi-model training, ROC/PR-AUC evaluation, calibration, cost-aware threshold tuning, error analysis, explainability, and live prediction.
This is an applied Machine Learning project
Synthetic data generation and baseline computer vision tooling for pH-sensitive freshness indicator films.
Сервис геокодирования московских адресов с нормализацией, сопоставлением, ранжированием кандидатов и Docker-запуском.
PersonaTTS is a personalized neural text-to-speech system that learns a user’s vocal persona from a short speech sample and generates natural speech for arbitrary input text.
Experimental web application demonstrating how an offline-trained financial fraud detection model can be exposed through a web interface. Built with Flask and a pre-trained XGBoost model to showcase ML inference flow, feature engineering, and result communication — not a production fraud prevention system.
A curated collection of applied machine learning projects, ranging from core ML fundamentals to deep learning, reinforcement learning, NLP, and computer vision. Built as a professional learning portfolio demonstrating growth, experimentation, and real‑world problem‑solving.
Двухэтапная рекомендательная система на MovieLens с отдельным отбором кандидатов, переранжированием и API выдачи.
RAG-контур с переформулировкой запроса, переранжированием, цитированием и проверкой ответа по найденным источникам.
Система поиска похожих автомобилей по тексту, метаданным и визуальным признакам с оценкой качества и FastAPI API.
Applied time-series forecasting and anomaly detection using ML and statistical baselines, with rigorous experimentation, residual-driven diagnostics, and reproducible evaluation workflows.
Стенд для сравнения поиска BM25, векторного поиска, объединения сигналов и переранжирования на FAQ-корпусе.
An explainable anomaly-detection workbench for small time-series datasets with reproducible experiments and a browser-based report.
Interpretable credit risk modeling using real-world lending data, with emphasis on probability calibration, decision relevance, and scalable machine learning workflows.
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