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Summary of approach: Our solution for Phase 1 is a gradient boosted decisiontree approach with a lot of feature engineering. We used the LightGBM library for boosted decisiontrees because it has absolute error as a built-in objective function and it is much faster for model training than similar tree ensemble based algorithms.
SaaS takes advantage of cloudcomputing infrastructure and economies of scale to provide clients a more streamlined approach to adopting, using and paying for software. Software as a service (SaaS) applications have become a boon for enterprises looking to maximize network agility while minimizing costs.
Familiarity with cloudcomputing tools supports scalable model deployment. DecisionTrees These trees split data into branches based on feature values, providing clear decision rules. A solid foundation in mathematics enhances model optimisation and performance.
A key aspect of this evolution is the increased adoption of cloudcomputing, which allows businesses to store and process vast amounts of data efficiently. Dive Deep into Machine Learning and AI Technologies Study core Machine Learning concepts, including algorithms like linear regression and decisiontrees.
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