Carolyn has a deep passion for helping analysts and analytical teams engage with the wider business and stakeholders to deliver solutions that provide value and bottom-line benefits. Her style can best be described as rational, logical, and precise, whilst also being adventurous, imaginative and innovative, leveraging the facts to see the possible futures ahead. Having held various analytical and leadership roles in the academic and corporate world, across multiple industries and geographies, Carolyn's initial focus was to deliver quality and robust analytics. Over time, she realised that meaningful change required more than just great technical skills. Carolyn has over 20 years of experience in retail consumer credit risk analytics and machine learning. Through her training, coaching and mentoring programs, Carolyn is passionate about galvanising analysts and technical leads to be more impactful in their journeys and endeavours. Carolyn's first book, It's a Risky Business, was published in November 2022.
Are you a developer who wants to break into machine learning and data science?
In this talk, I cover the most important aspects of Machine Learning that don't involve code:
- What is data wrangling, and why is it important?
- Why are data transformations so important?
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What are the most commonly used ML algorithms, and why should I use one and not another?
- Why overfitting is bad and how to avoid it
Machine learning is not about the language or tool you use to create the models: R, Python, SAS, Knime; they're all just tools. It's how you use those tools that matters.
