Jigyasa Grover is a Machine Learning Engineer at Twitter, co-author of Sculpting Data for ML and an ML Google Developer Expert. Prior experiences include stints at Facebook, Inc., National Research Council of Canada, and Institute of Research & Development France involving Data Science, mathematical modeling, and software engineering.
A Red Hat Women in Open Source Academic Award Winner and a Google Summer of Code alumna, Jigyasa is an ardent open-source contributor. In her quest to help build a powerful community of girls and boys alike, and believing in “we rise by lifting others”, she mentors aspiring developers and Machine Learning enthusiasts in various global programs. She has served as the Director of Women Who Code and Lead of Women Techmakers.
She has a Master’s degree in Computer Science with an AI specialization from the University of California, San Diego, and is currently applying her past experiences and knowledge to Applied Machine Learning in the online advertisements prediction and ranking domain.
In the contemporary world of learning algorithms, along with the aggregate domains plying machine learning, the complexity of the models has been inching up. Thus it is important to approach machine learning in a conceptual way. In this talk,
I’ll present an informal taxonomy of machine learning algorithms, grouped on the basis of the different mathematical abstractions.
I will cover logical models, with tree based or rule based concepts, geometric models, including linear and distance based approaches, and probabilistic models. I will go over the fundamentals of each type of model and discuss their pros and cons and use cases along with a very simple hands-on example.
The talk will conclude with some pointers on how to explore the data and choose a model to make the learning more efficient.
Sculpting Data for ML is the title of a new book I co-authored with Rishabh Misra, my colleague at Twitter. Want to learn how to create your very own quality datasets using Python and other open source tools? This is the book to have. It’s available at Amazon.
Sculpting Data for Machine Learning is the title of a workshop I’ll conduct with my colleague Rishabh Misra on Feb. 10 during Algorithm 2022. Click the button for workshop info.
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