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Intern – Automatic Hyperparameter Tuning for Demand Forecasting

4/5-month duration from February 2024


The intern will work on implementing a mechanism for automatic hyperparameter tuning in the AI Engine, which is responsible for ML-based demand forecasting. The goal is to make the engine autonomous and adaptive to each customer's needs by automatically setting hyperparameters. This will involve creating a system that uses techniques like holdout mode to calculate error metrics, avoid overfitting and underfitting problems, and adapt to new projects. Additionally, the intern will need to devise a strategy for the engine to monitor errors during weekly batches and adjust parameters, if necessary, limited to a set number of runs each week.

Skills and Requirements:

  • Strong programming skills, preferably in Python.
  • Knowledge of machine learning techniques, especially factorization machines.
  • Understanding of hyperparameter tuning methods, such as grid search or Bayesian optimization.
  • Familiarity with holdout validation techniques and error metric calculation.
  • Ability to create scripts for automated parameter adjustments. Analytical thinking and problem-solving skills

About Infor

Infor is a global leader in business cloud software products for companies in industry specific markets. Infor builds complete industry suites in the cloud and efficiently deploys technology that puts the user experience first, leverages data science, and integrates easily into existing systems. Over 60,000 organizations worldwide rely on Infor to help overcome market disruptions and achieve business-wide digital transformation. 
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