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@article{186216,
        author = {Prathamesh Bhamare and Proff. Sheetal Shevkari and Prajwal Mane},
        title = {How Machine Learning with Python and Artificial Intelligence Benefits Formula 1 Teams.},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {1226-1234},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=186216},
        abstract = {This research examines how the pinnacle of motorsport, Formula 1, maintains its competitive edge and how various teams utilize the latest technologies, data, and other advanced features to outperform one another. Teams make strategic calls, utilize information to try to dominate competitors, and make precise in-race decisions, helping drivers become increasingly familiar with car performance over time, which benefits them in the future during specific parts of the race track. We will also learn how technology has evolved Formula 1 as a sport, and how well certain teams perform using technology in areas like tyre degradation, race pace, and predicting grid positions during qualifying and many more aspects. Because of the increased need for technology, more and more Formula 1 teams are collaborating with companies that have extensive knowledge in the areas discussed in this research paper. For example, the McLaren Formula 1 team collaborates with Google Cloud for technological advantages, while the Mercedes-AMG Formula 1 team collaborates with G42, which has helped them leverage artificial intelligence to achieve greater track performance. We will see more of Python with Machine Learning and Artificial Intelligence in this research paper.},
        keywords = {Motorsports Analytics, Machine Learning, Python Programming, Telemetry Analysis, Predictive Modelling, Artificial Intelligence, Formula 1, Race Strategy Optimization, Technology Partnerships, Sports Analytics},
        month = {November},
        }