About the Reviewers

Chetan Khatri is a data science researcher who has a total of 4.6 years of experience in research and development. He works as a principal engineer, data and machine learning, at Nazara Technologies Pvt. Ltd, where he leads data science practice in the gaming business and the subscription telecom business. He has worked with a leading data company and a Big 4 company, where he managed the Data Science Practice Platform and one of the Big 4 company's resources team. Previously, he was worked with R & D Lab and Eccella Corporation. He completed his master's degree in computer science and minor data science at KSKV Kachchh University as a gold medalist.

He contributes to society in various ways, including giving talks to sophomore students at universities and giving talks on the various fields of data science in academia and at various conferences, thus helping the community by providing a data science platform. He has excellent correlative knowledge of both academic research and industry best practices. He loves to participate in Data Science Hackathons. He is one of the founding members of PyKutch—A Python Community. Currently, he is exploring deep neural networks and reinforcement learning with parallel and distributed computing for government data.

I would like to thanks Prof. Devji Chhanga, Head of the Computer Science Department, University of Kachchh, for routing me to the correct path and for his valuable guidance in the field of data science research. I would also like to thank my beloved family.

Pavan Kumar Kolluru is an interdisciplinary engineer with expertise in Big Data; digital images and processing; remote sensing (hyperspectral data and images); and programming in Python, R, and MATLAB. His major emphasis is on Big Data, using machine learning techniques, and its algorithm development.

His quest is to find a link between different disciplines so as to make their processes much easier computationally and automatic.

As a data (image and signal) processing professional/trainer, he has worked on multi/hyper spectral data, which gave him expertise in processing, information extraction, and segmentation with advanced processing using OOA, random sets, and Markov random fields.

As a programmer/trainer, he concentrates on Python and R languages, serving both the corporate and educational fraternities. He also trained various batches in Python and packages (signal, image, data analytics, and so on).

As a machine learning researcher/trainer, he has expertise in classifications (Sup and Unsup), modeling and data understanding, regressions, and data dimensionality reduction (DR). This lead him to develop a novel machine learning algorithm on Big Data (images or signals) that performs DR and classifications in a single framework in his M.Sc. research, fetching distinction marks for it. He trained engineers from various corporate giants on Big Data analysis using Hadoop and MapReduce. His expertise in Big Data analysis is in HDFS, Pig, Hive, and Spark.

Dipanjan Sarkar is an Data Scientist at Intel, the world's largest silicon company which is on a mission to make the world more connected and productive. He primarily works on analytics, business intelligence, application development, and building large scale intelligent systems. He received his Master's degree in Information Technology from the International Institute of Information Technology, Bangalore. His area of specialization includes software engineering, data science, machine learning, and text analytics.

Dipanjan's interests include learning about new technology, disruptive start-ups, data science, and more recently deep learning. In his spare time he loves reading, writing, gaming, and watching popular sitcoms. He has authored a book on Machine Learning titled R Machine Learning by Example,Packt Publishing and also acted as a technical reviewer for several books on machine learning and Data Science from Packt Publishing.