About the Authors

Hunaidkhan Pathan currently serves as a Data Science Lead for a leading consulting firm with over a decade of experience in the field. Specializing in machine learning and artificial intelligence, he brings a wealth of expertise to his role. Hunaidkhan holds a PGDM in Data Science from Shanti Business School in Ahmedabad and a degree in Electronics and Communication Engineering from Gujarat Technological University.

He has significantly contributed to the data science community, with his research papers selected and presented at the prestigious SAS Analytics Conference 2013 in Orlando. The titles of his papers include “Marketing Mix Modeling” as an author and “Predicting market uncertainty with Kalman filter” as a co-author. He was also a LinkedIn Top Voice for Data Science and Artificial Intelligence in 2023. He posts regularly on LinkedIn about Generative AI.

Hunaidkhan is an acknowledged Subject Matter Expert (SME) in Generative AI and Natural Language Processing. His diverse experience spans various LLM services such as OpenAI, Nvidia Nemo, Anthropic, GCP Generative AI, and AWS Bedrock, in addition to numerous open-source LLMs. His broad experience and profound knowledge make him a valuable contributor in the domain of data science.

Nayankumar Gajjar, has a rich background in Data Science, Machine Learning and Generative AI fields with 9 years of extensive experience as a Data Scientist, Machine Learning Engineer, and Python Developer. Over the years, he has made significant contributions to various high-impact projects, showcasing his expertise in statistical modeling, Generative AI, MLOps, and Cloud Computing. This diverse skill set makes him a versatile and highly skilled professional in the Data Science and Machine Learning domains. He holds a master’s degree in Decision Science, further solidifying his deep understanding of the field. In addition to his professional work, he is a YouTuber and a blogger who shares his experiences and knowledge, offering a complete understanding of statistics and providing detailed coding tutorials. His commitment to education extends to his role as a visiting faculty member, where he has taught Python, SQL, Data Science, and NLP courses. He also co-authored a research paper titled “Thiessen Polygon, A GIS approach for Retail Industry in SAS,” which was presented at the prestigious SAS Analytics Conference 2013 in Orlando.