Code, Coffee, and Quarantine (Virtual edition)

This is a virtual gathering to chat and learn from each other while social distancing. Our goal is to provide a place where we can network, get help with our projects, and learn from each other.

This week we'll hear a talk by Jigyasa Grover, who will tell us about a book she recently launched called "Sculpting Data for ML: The first act of Machine Learning." It introduces the readers to the first act of Machine Learning, Dataset Curation. She'll be sharing some lessons/what you can learn in her book.

We'll meet and chat for the first half of the meeting and then we'll move into the talk/question and answer part of the session. The event is scheduled for one hour, but if the discussion goes longer we can stay until 12:30.

Talk overview

Talk Blurb: Without a doubt, many recent breakthroughs in Machine Learning owe as much to having better data as they owe to having better models. A common experience among ML practitioners these days is that "data munging" occupies more time and effort than modeling. Despite these facts, data curation often does not get the limelight, be it Academia or the Industry. Jigyasa will put forward the importance of data in the Machine Learning ecosystem. She will also talk about her recently launched book "Sculpting Data for ML: The first act of Machine Learning" which helps identify valuable information from the extensive amount of crude data available at our fingertips.

Bio: Jigyasa Grover is a Machine Learning Engineer at Twitter and the author of the book 'Sculpting Data for ML'. She has a myriad of experiences from her brief stints at Facebook, Inc., National Research Council of Canada, and Institute of Research & Development France involving Data Science, mathematical modeling, and software engineering. Having graduated from the University of California, San Diego, with a Master's degree in Computer Science with an Artificial Intelligence specialization, she is presently plying her past experiences and knowledge towards Applied Machine Learning in the online advertisements prediction and ranking domain. Red Hat 'Women in Open Source' Academic Award Winner and Google Summer of Code alumna, Jigyasa is an ardent open-source contributor as well. She served as the Director of Women Who Code and Lead of Women Techmakers for a handful of years to help bridge the gender gap in technology. In her quest to 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 also has many international conference keynotes, technical talks, panels, workshops, blogs, and podcasts to her name. Apart from her technological ventures, she enjoys exploring new places, hanging out with friends and family, and has been recently having fun with baking. You can reach her out on Twitter (@jigyasa_grover).

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We hope you’ll join us!