Machine Learning for Security
Overview
In this episode of the Data Bytes Podcast, we sit down with Carly Taylor, Founder of Rebel Data Science and a seasoned expert in the field of machine learning for security. With a rich background that includes roles at Activision, Well Data Labs, and more, Carly brings a wealth of experience to the table.
Our conversation delves into the intricacies of implementing machine learning models, from ideation to deployment. Carly shares key steps and emerging technologies that are shaping the future of machine learning implementation.
Security is paramount in today's data-driven world, and we explore the potential risks associated with deploying machine learning models in production environments. Carly discusses the role of federated learning in addressing privacy concerns and highlights crucial considerations for securing data pipelines used in training and deploying these models.
For aspiring professionals in machine learning security, Carly offers valuable strategies to effectively prioritize learning and skill development in this dynamic field. She also shares insights on fostering cross-disciplinary collaboration with other teams, such as data science, engineering, and cybersecurity.
Join us for an insightful conversation that not only explores best practices in machine learning security but also provides personal anecdotes and career advice from an industry expert. Whether you're a seasoned pro or just starting your journey in machine learning, this episode is packed with valuable insights to advance your career in data security.
About Carly
Carly is a data scientist, computational chemist and machine learning engineer. She obtained her M.S. in chemistry from the University of Colorado focusing on computational quantum dynamics. She has authored multiple peer-reviewed publications and holds two non-provisional machine learning patents.
When she isn't writing about herself in the third person, building mechanical keyboards, or neglecting the Oxford comma, she works as a security strategist for Call of Duty at Activision Publishing.
More specifically, she applies Python-based machine learning and best practices in statistical analysis to creatively solve novel problems. This includes harnessing various toolkits to model real-world structured and unstructured data and drive business value to stakeholders at all levels of the organization.
Areas of Expertise: data science, machine learning, fraud detection, trust & safety, distributed systems, leadership, team-building, time-series and dynamic modeling, anomaly detection, biotechnology, and high-frequency signal processing.
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