Embracing MLOps: Bridging the Gap Between Machine Learning and DevOps

In the dynamic field of machine learning, MLOps (Machine Learning Operations) has emerged as a crucial discipline combining aspects of machine learning, data science and operations. This talk aims to demystify MLOps differentiating it from traditional DevOps practices and highlighting its growing importance.

About Mayank Jindal

Mayank Jindal is a software engineer at Amazon with nearly 4 years of experience. His primary focus has been on improving advertising moderation efficiency across Amazon using AI-based techniques and building scalable software around that. Mayank has worked with major cloud technologies and gained expertise in building cloud-based microservices.

Mayank has made significant contributions to the open-source community through participating in Google Summer of Code. He has contributed over 20,000 lines of code to the "Mifos Initiative," a non-profit organization striving to provide financial services to underprivileged populations. His contributions extend to mentoring the next generation of open-source contributors through Google Code-In.

He also had the privilege of speaking at tech conference and podcast which allowed him to share his knowledge and insights with a wider audience.

Mayank holds a Master's degree in Computer Science from the University of Chicago and a Bachelor's degree in Civil Engineering from the Indian Institute of Technology, Kharagpur.