Lifecycle of a Data Science Project

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    Duration : 60 mins

    Do you know – what does it take to deploy a Data Science model? How do the Machine Learning models go live?, What happens if the model fails? And why do they fail? How is the real world different from data science hackathons and contest?
    Join Mathangi Sri on a webinar where we can discuss the Machine Learning project in depth –
    1. Where does the project originate
    2. Who all should be involved as part of the project
    3. The essence of a cross-functional team
    4. Measurement strategies
    5. Last but the most important – how to optimize the model for a better performance

    Key Takeaways

    1. You will appreciate the variety of the team that needs to make AI & ML model go live – from analysts to engineers to designers to project managers.
    2. The planning that needs to go in for an impactful model.
    3. How to define success and the nuances around it.
    4. The essence of feedback and data instrumentation for continuous learning.

    Webinar Leader

    Mathangi Sri

    Data Science Lead, Phonepe