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UCSDMachineLearning

Harness machine learning to predict stock price trends. Train a powerful model using scikit-learn and Gradient Boosting Regression. Input historical stock data for accurate predictions of days from start date. Elevate your decisions with data-driven insights.

Last updated March 9, 2026

Overview

Harness machine learning to predict stock price trends. Train a powerful model using scikit-learn and Gradient Boosting Regression. Input historical stock data for accurate predictions of days from start date. Elevate your decisions with data-driven insights.

Tech Stack

Python

Primary language: Python

Engineering Decisions

  • Prioritize maintainability and clear interfaces for long-term evolution.
  • Design around observability and operational correctness from early stages.
  • Balance product velocity with platform reliability tradeoffs.

Outcomes and Future Direction

  • Demonstrates end-to-end ownership across architecture and product execution.
  • Shows practical capability in shipping production-style systems.
  • Future work includes deeper benchmarks, testing, and system hardening.