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This project features a machine learning pipeline that utilizes a Random Forest Classifier to predict milk yield fluctuations and detect subclinical mastitis in dairy cattle. By integrating multi-parameter data including Somatic Cell Count (SCC), electrical conductivity, and lactation stages,the model identifies early-stage health deviations that often bypass manual inspection. This proactive approach enables precision livestock management, allowing for targeted veterinary intervention to minimize production losses and improve overall animal welfare.
The network for creativity
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Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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Agent products resist normal product marketing. There's no single interface to screenshot and the category vocabulary has gone generic, so a feature list communicates almost nothing.
We built Heron's explanation as a four-beat scroll that runs the agent's actual loop. The model appears and is watched. Violations surface with plain language and a real IBC clause. An edit is applied after approval. The system learns the firm's standards.
Pacing was the main design problem. Each beat needed enough scroll distance to register as a separate action, without the section becoming so long that people bail before the payoff. The sequence carries the technical detail that would otherwise sit in a spec table.
The four-beat scroll is a smart way to make the agent’s loop feel tangible—much clearer than a static feature list. The restrained visual system gives the interaction room to breathe.
What does luxury look like?
A cinematic AI product of a modern apartment designed to make you stop, look, and imagine yourself there. ✨
Would you live here?
A production-ready machine learning web application that predicts the likelihood of heart disease based on patient medical data. Built using Python, Streamlit, and Scikit-learn, the app provides real-time predictions with high accuracy and a clean, user-friendly interface.
