Udacity Self-Driving Car Simulator
Trained a neural network to steer a simulated car from camera input — an end-to-end deep-learning pipeline from data collection to a model driving the track.
Machine learning, analysis, and AI engineering — each case study documents the problem, the approach, and the honestly-measured outcome. Scraping work lives in the scraper library and the Apify portfolio.

PyTorch hybrid recommender (sequence + content + collaborative signals) for 95,415 MOOC learners, served through a Flask REST API — beats item-CF on every metric.

Seven Keras architectures compared for early failure detection on ciphered wind-turbine sensor data — 93.6% recall on unseen failures.

Retrieval-augmented clinical Q&A with a local Mistral-7B over 4,114 pages — four-stage evaluation with documented failure analysis.

Leakage-safe pipeline that flags invalid German vehicle-repair invoices: automated quality checks, time-based validation, calibrated thresholds.
Half-hourly grid-demand forecasting with lag, cyclic and decomposition features — LightGBM wins at 0.21% MAPE on validation.

Statistical study of 10,000 psychiatric patient records: hypothesis tests, feature screening, and an OLS model explaining 63% of GAF variance.
Spark-based exploration of 28,823 Twitter conversations: cleaning, derived toxicity flags, and matched DataFrame-API vs SparkSQL analyses.
Work-in-progress 3D CNN pipeline for lung-CT nodule classification: parallel dataset assembly from Zenodo, SimpleITK volume loading, 128³ inputs.
Trained a neural network to steer a simulated car from camera input — an end-to-end deep-learning pipeline from data collection to a model driving the track.
Explored clinical records to identify which patient characteristics correlate with mortality risk, turning raw hospital data into interpretable risk factors.
Analyzed accident records to surface the conditions and locations where crashes cluster — evidence a safety program can act on.
Built models on live London accident data to predict severity and link outcomes to weather conditions as they change.
The extraction side of the practice ships as products: 200+ documented scrapers, published as Apify Actors used by 3.5K+ people.
Every project here started as a short plain-English brief. Send yours and get a feasibility answer with a fixed quote.