AAII Technical Lecture Series (ATLS-3)
The use of machine learning (ML) technology has already been increasing over the past few years. This technological advancement increases the number of jobs in >diverse industrial sectors, where ML is the primary component—thereby growing the demand for engineers/scientists/researchers with expertise in ML.
In this version of ATLS, our invited speaker gave a brief overview of different aspects of ML interview and how one should structure his/her interview preparation process.
The outline of the talk was -
- General Preparations
- Interview process
- Machine Learning
- Research
- Coding
- Case Studies
Dr. Banriskhem emphasized the importance of studying/analyzing ML case studies while preparing for the interviews. He also explained how one should formulate an ML case study problem and execute it in a structured manner by discussing a few case studies’ examples.
- How logistic regression model can be estimated by the probabilistic framework called maximum likelihood estimation
- Decision tree
- Scrambled sentences having the same kind of permutation
- Language modeling
Related links:
Speaker
Dr. Banriskhem K. Khonglah is a Senior Researcher at Cerence Inc, Germany, the automotive division of Nuance, working in Language Modeling for Automatic Speech Recognition (ASR). He did his Ph.D. from IIT Guwahati in the area of speech music classification. Before joining Cerence Inc, he worked as a post-doctoral researcher at Idiap Research Institute, Switzerland, in the IARPA project “MAchine Translation for English Retrieval of Information in Any Language” (MATERIAL) for ASR and as a Data Scientist at KOViD Analytics, Guwahati. He has a demonstrated history of working in the research industry with applications such as audio classification, speech enhancement, and speech recognition. He published papers in reputed journals and conferences. Linkedin, Google Scholar
Speaker: Dr. Banriskhem K. Khonglah, Senior Researcher, Cerence Inc, Germany
Topic: Requisites for General Machine Learning Interviews
Date: 13 December 2020
Time: 5 PM (IST)