Ask Me Anything About the Math Needed for Data Science

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Learning the theoretical background for data science or machine learning can be a daunting experience as it involves multiple fields of mathematics.

Metis Senior Data Scientist Kimberly Fessel holds a Ph.D. in applied mathematics from Rensselaer Polytechnic Institute and completed a postdoctoral fellowship in math biology at the Ohio State University. In this AMA Kim will answer your questions about the mathematics needed to start your journey into the world of data science.

Below is a quick overview of the math needed for data science.

Linear Algebra
Used in machine learning (& deep learning) to understand how algorithms work under the hood. Basically, it’s all about vector/matrix/tensor operations, no black magic is involved!

Calculus
Used in machine learning (&deep learning) to formulate the functions used to train algorithms to reach their objective, known by loss/cost/objective functions.

Statistics and Probability
Used in data science to analyze and visualize data, in order to discover (infer) helpful insights.

Kimberly uses her background in applied math to discover data's what, why, and how.

Kimberly joins Metis from MRM//McCann, a leading digital advertising agency, where she focused on helping clients understand their customers by leveraging unstructured data with modern NLP techniques. She is passionate about data storytelling and the power of compelling data visualizations to challenge pre-conceived assumptions. Kimberly's enthusiasm for teaching comes from her days as an academic. She holds a Ph.D. in applied mathematics from Rensselaer Polytechnic Institute and completed a postdoctoral fellowship in math biology at the Ohio State University. In her spare time, Kimberly likes to stay active and particularly enjoys swing dancing, rollerblading, and jogging with her dog.

About Metis

Metis (thisismetis.com) accelerates careers in data science by providing full-time immersive bootcamps, evening part-time professional development courses, online resources, and corporate programs based in Seattle, New York, Chicago, and San Francisco.

Brought to you by Kaplan, Metis focuses primarily on Python, machine learning, data visualization, deep learning, big data processing, statistical foundations, and more. Students and alumni of the bootcamp program receive continuous support from our career advisors, empowering them to pursue a successful career in the fast-growing field of data science.

Learn more about us at

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