Machine Learning Model Deployment
Deployment Date: 2022-01-10 09:10:33 UTC
Artificial Intelligence |
Statistical Modeling |
Text Analytics |
Big Data |
Digital Analytics |
Visualization |
Python |
R |
Tableau |
Retail |
Category: Domain Usecases
Sub-Category: Sports
Use-case Type: Structured Data Predictions
Public API
Note: Certain Model Inferences can take long time for the first run (Warmup) and would get faster with the subsequent inferences. We thank you for your patience.
Baseball is a bat-and-ball game played between two opposing teams, typically of nine players each, that take turns batting and fielding.
The project aims to predict total runs scored by baseball players.
The dataset utilised here was collected from the Lahman Baseball Database and contains 4535 rows of data for a select sample of players from 1960 to 2004.
'r2_score' has been used to check the model's performance.
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