Title: Practical Machine Learning approaches in Micro-biology

Biography:

Mr. Deepak S. Mane is a Senior Data Scientist/Enterprise Solution Architect in Global Consulting practice - Performance Engineering Lab at Tata Research Development and Design Center (A Research wing of TCS). In his previous role he was Scientific Officer at Tata Institute of Fundamental Research (TIFR). Mr. Deepak Mane has 17+ years of experience as Data Scientist/Enteprise Solution architect in Data Science , Data Management , governance , Science and Analytics , Big Data , Cloud Computing , Artificial Intelligence , Machine Learning , Deep Learning. Currently, he is working as Senior Data Scientist Commonwealth Bank of Australia through TCS. He has 7+ onsite experience at various locations  such as USA, Europe, Australia and Asia in big data and cloud domain. Mr.Deepak Mane holds 6 certifications in the Data Science and cloud computing domain. He has published 21 papers in Conferences Seminars , and has been conducting Seminars/workshops at various colleges in Maharashtra and MP under AIP/FDP activities - TCS . He's also a mentor for KreSIT, Indian Institute of Technology - Mumbai. He is working as Reviewer for 10 Scopus and Springer Journals including cyber war , cyber security , artificial Intelligence. 

Abstract

Microbiology is the study of micro-organisms like archaea, bacteria, fungi, protozoa and viruses. People studied micro-biology through existing methodologies like cultivation but this methods are very expensive and time-consuming.  With help of Due to the invention of this high thorough-put sequencing technology, a large amount of microbial data is being generated thus, machine learning is branch of artificial intelligence has steadily won its way into the area of microbial analysis as the go-to method to solve classification and interaction problems. Literature reviews have shown that ML can be used in many aspects of microbiology research, especially classification problems, and for exploring the interaction between microorganisms and the surrounding environment. In this talk , We will discuss about various machine learning algorithms with business use cases , open source tools covering all areas of microbiology