Abstract: 

Regardless of your industry or functional areas, in order to build modern products and services, product managers will benefit the most by taking a data-driven decision-making process. The A/B testing or random controlled trial (RCT), is the core of the product development process. Instead of limiting to traditional A/B testing alone, using techniques such as Reinforced Learning (RL) techniques, multi-arm bandits, Markov Decision Process, exploration, and exploitation, enterprises are able to build superior products with low opportunity costs. In this session, the audience will be able to learn emerging techniques to building superior products.

Bio: 

A proven leader in Data Sciences & Applied AI. Experience in managing large scale projects and teams in data engineering, ML operations, and ML modeling. Helped in developing and implementing enterprise AI strategy; I have lead Cloud Migration and Integration efforts. Good understanding of State of the Art (SOTA) ML tools, framework, and algorithms. Experience in building distributed machine learning workflows using Apache Spark, DASK, Rapids and Kubernetes.

Vamsi enjoys reading the latest ML papers and staying up-to-date with relevant trends in the field.
Leading research in SOTA in areas such as Natural Language Inference, Text Entailment, Q&A, Text Classification, and Semantic Similarity using BERT, RoBERTa, Fairseq, Huggingface, LSTM, Transformers and others.

In the past established highly talented engineering teams at various enterprises. Vamsi has a successful track record of tactical execution in fast-paced software and technology development environments.