Data Science and ML in Cricket

 Objective of the data science in cricket  - Increate team performance  - Maximiser winning chances  Here's a simplified version: --- The IPL has expanded cricket, increasing the number of matches and the amount of data collected. Modern cricket data analysis involves tracking various factors like player positions, ball movements, shot types, delivery angle, spin, speed, and trajectory, which makes data cleaning and preprocessing more complex. **Dynamic Modeling** In cricket, numerous variables must be tracked, including player actions, ball attributes, and potential outcomes. The complexity of modeling depends on the type of predictive questions asked. Predictive models become especially challenging when analyzing hypothetical scenarios, like how a batsman’s shot might change with different ball angles or speeds. **Predictive Analytics Complexity** Cricket decision-making often relies on queries like "how often does a batsman play a specific shot against a certain b...
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Artificial intelligence in in the software testing

Welcome to the world of artificial intelligence and the software testing enter enter



How AI is helping qa to design and developed test cases 


  • Conduct the initial document review and understand the requirement of the software 
  • Understand the pattern of bugs and understand the prediction of occurrence of the bug 
  • Execute the test cases and prepare reports 
  • Conduct the initial testing before the software release and understand the enhancements if any.

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