Predicting the outcomes of a tennis match
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Post a project like this1068
£155(approx. $195)
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- Proposals: 9
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- #3259514
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Regensburg
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Ahmedabad
55145726649842543778371088649082965079615516811152704885478803
Description
Experience Level: Entry
I have a data set, which is live and updates daily. I need a pipeline to process data, clean the data, and build machine learning models to predict the outcome of a tennis match. 4 target outcomes are required including match winner and set score for both men and women's matches.
I ideally want the models as lstms but other neural network structures are possible. I have already tested various other methods including boosting and bagging but want expertise in deep neural networks.
I will supply a static dataset to you which you clean, process, train and test various models to outperform my own existing models which currently achieves just over 69 percent accuracy on match winner test sets.
The outputs
- modular source code (python), including cleaning, processing and training/testing models
- detailed commentary on code
- full data quality assessment
- detailed assessment of any feature generation
- assessment of statistical properties
- visualations of data
- models (match winner and set score/set difference)
- Recommendations for further enrichment and productionalising
If this proves successful there will be further opportunities to develop this framework further.
To bid for the project please provide a brief description of your expertise in machine learning (ideally deep learning) and examples of predicting the outcomes of events.
I ideally want the models as lstms but other neural network structures are possible. I have already tested various other methods including boosting and bagging but want expertise in deep neural networks.
I will supply a static dataset to you which you clean, process, train and test various models to outperform my own existing models which currently achieves just over 69 percent accuracy on match winner test sets.
The outputs
- modular source code (python), including cleaning, processing and training/testing models
- detailed commentary on code
- full data quality assessment
- detailed assessment of any feature generation
- assessment of statistical properties
- visualations of data
- models (match winner and set score/set difference)
- Recommendations for further enrichment and productionalising
If this proves successful there will be further opportunities to develop this framework further.
To bid for the project please provide a brief description of your expertise in machine learning (ideally deep learning) and examples of predicting the outcomes of events.
Samir T.
100% (5)Projects Completed
6
Freelancers worked with
4
Projects awarded
43%
Last project
8 Apr 2024
United Kingdom
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