Sculpting Data for Machine Learning

In the contemporary world of Artificial Intelligence and Machine Learning, data is the new oil. For Machine Learning algorithms to work their magic, it is imperative to lay a firm foundation with relevant data. Sculpting Data for ML introduces the readers to the first act of Machine Learning, Dataset Curation.

This month we are joined by Jigyasa Grover, a Machine Learning Engineer working at Twitter in San Francisco to discuss:

• Significance of data in Machine Learning
• Identification of relevant data signals
• End-to-end process of data collection and dataset construction
• Overview of extraction tools like BeautifulSoup and Selenium
• Step-by-step guide with Python code examples of real-world use cases
• Synopsis of Data Preprocessing and Feature Engineering techniques
• Introduction to Machine Learning paradigms from a data perspective

Jigyasa has the honor of being recognized as one of the Google Developer Experts in the Machine Learning domain. She recently co-authored a book titled Sculpting Data for ML: The first act of Machine Learning which is a culmination of her myriad of experiences from 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, Jigyasa is presently applying her past experiences and knowledge towards Applied Machine Learning in the online advertisements prediction and ranking domain.

A 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.