I have strong hands-on experience in the development of SaaS-based optimized AI and analytics products in several verticals. For the last 6.5 years, I have been working on complex problems related to various domains such as retail, healthcare, human resources, pharma, telecom, sales, and others for creating real-time products. I am a co-author of a machine learning book entitled "Practical Machine Learning with Spark". I am also a research reviewer for the Journal of Big Data and other international conferences. I have been associated as a guest researcher at one of the reputed universities in Europe and have published several research papers on DL/AI in many reputed journals and conferences such as IEEE, Elsevier, and IJCB. I love to write research articles, whitepapers, give technical talks, blogs, and technical books, and relish reading spiritual books. In my leisure time, I like to do trekking and meditation in the Himalayan ranges. At ArogyaPandit, we have strong expertise in dealing with the migration of legacy on-premise Hadoop to cloud environments (AWS, Azure, and GCP) in an efficient time frame and cost. Please contact us at [login to view URL].
These are the list of tools which I have had used in projects:
Big Data Landscape:
Ambari, Cloudera, Hortonworks, Apache Pig, Apache Sqoop, Apache Spark2.0, Apache Hive, Apache Kudo and Impala, Apache Kylin, Apache Kafka, Confluent Kafka, Schema Registry, Apache Oozie, Apache Airflow, Apache Livy, Apache Nifi, Apache Minifi, Hbase, MongoDB and Cassandra, Elastic Search, LogStash, Solr
DeepLearning:
Mathematical modeling for building Neural layer, Meta-Learning, Computer Vision, SkLearn, Reinforcement Learning, Few-shot Learning, Zero-shot learning, GAN, Transfer Learning, Instance Segmentation, Semantic Segmentation, Classification, and Detection.
IoT Frameworks:
DeviceHive, KAA, SiteWhere, Cumlocity, NIFI , MiNIFI, Big Data IoT pipelines, and distributing processing through Edge Computing.
Digital Twin:
Google Firebase, Revitt, AutoDesk, Kafka, Raspberry Pi Configurations, Augment Reality, and Virtual Reality.
Cloud Framework :
AWS, Azure, GCP and IBM Watson.
Data Visualization:
PowerBI, Tableau, SpagoBI, Kibana, Grafana, Fusion Chart, Embedded Charts, and Google Looker.
Front-end:
ReactJS, Angular, NodeJS, Flask, Fusion, Plotly, and CSS.
Miscellaneous :
Speech Analytics, Natural Language Processing, Recommendation Engine, Transcript to Audio Conversion.
