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- Webinar -


Boot Camp on Cricket Score Prediction Via Machine Learning



Boot Camp on Cricket Score Prediction Via Machine Learning

While we are currently living in a world that foresees technology to be the future of the workforce and recruitment. Industries like Artificial Intelligence and Machine Learning will set a benchmark in leading technology and economy hand-in-hand. Starting from the basics of Machine Learning, let us ...

07:00 PM, 31 Oct 2020

FREE

26 October, 2020

While we are currently living in a world that foresees technology to be the future of the workforce and recruitment. Industries like Artificial Intelligence and Machine Learning will set a benchmark in leading technology and economy hand-in-hand. Starting from the basics of Machine Learning, let us take a look at the prediction strategy for a premier game like Cricket on various applications. This webinar on <add name, date and time> will allow you to comprehend the dynamics of Machine Learning as a tool to develop, predict and strategise while predicting the winning team, score or the flow of the game. The main objective of sports prediction is to improve team performance and enhance the chances of winning the game. The process and tools behind the prediction include the following: ·         Jupyter Notebook ·         Numpy ·         Pandas ·         Seaborn ·         Matplotlib ·         Scikit-learn The Bootcamp will focus on the following features to help you build a prediction module for games like cricket. ·         Data cleaning and formatting ·         Exploratory data analysis ·         Feature engineering and selection ·         Compare several machine learning models on a performance metric ·         Perform hyperparameter tuning on the best model ·         Evaluate the best model on the testing set ·         Interpret the model results ·         Draw conclusions and document work Want to understand the tools and technology behind these features? Sign-up for our Bootcamp today and stay tuned for the same.



PRICE: FREE


TIMINGS: 07:00 PM, 31 Oct 2020



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