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Wrapping Up- Top ML Talks From Day 2 At AIM’s Plugin 2020

Wrapping Up- Top ML Talks From Day 2 At AIM’s Plugin 2020

Ambika Choudhury
W3Schools

One of the biggest online conferences brought to you by Analytics India Magazine, “Plugin” aims to bring the best brains together from all around the world to talk about cutting-edge innovations in a distinctive virtual setting. The two-day virtual event indeed gave the attendees direct access to the brilliant minds of AI and data science ecosystem.

The second and last day of the online conference “plugin” has started with a number of parallel tracks and lots of knowledge sharing through demos and workshops from the top analytics leaders of the industry. 

Below here we listed a quick glance to all the talks of Day 2 at Plugin 2020.



A Glance from the Tech Talks

How to develop Credit risk models (scorecard) using Machine learning technique and its use in underwriting strategy development

The first Tech Talk of the day was delivered by Sanjay Kar, Head of Analytics at Equifax India where he talked about how banking and finance domain became the early adopter of data analytics. He discussed various topics including credit risk management, approaches and steps to develop credit risk modelling, a brief on underwriting strategy, how to develop strategies, prepare data, as well as validation and calibration.

Identifying Model Drift Before It Is Too Late

In this talk, Jacqueline Long, Principal Solutions Architect- Global Tech Practice contactless commerce is reshaping consumer behaviour and the “new normal” has brought about an immediate need to adjust to the global COVID-19 situation. Jackqueline explained the phases of Governed ModelOps Process, what are its prototypes, deploy and production environment. She further discussed the meaning of model drift and how business decisions that rely on analytical models could be suffering from model drift.

The Value of Data Analytics in the Smart Factory

Sudhir Padaki, Director of Business dev- Data & Analytics at Altair discussed how to access data from the shop floor through OT/IT convergent solutions and build useful analytics to tackle Asset Monitoring, Predictive Maintenance and how one can leverage analytics on a shop-floor in real-time to identify hidden indicators for future downtimes or identify anomalies. He discussed the scenarios with a demo where he showed real-time asset monitoring, real-time scoring, among others. 

Approaching (Almost) Any NLP Problem

This talk was delivered by Abhishek Thakur, who is the world’s first 4x Kaggle Grandmaster and Chief Data Scientist at Boost.ai. In this talk, Abhishek discussed on one of the popular topics of machine learning techniques, Natural Language Processing (NLP) along with various other machine learning techniques. He talked about the uses and applications of NLP, how to perform pre-processing on text data and solve a complex problem, various machine learning and deep learning models along with a demo on Quora duplicate question identification.

Leveraging Game Theory for Explainable AI (XAI)

Shashank Shekhar, Head-Advanced Analytics & Data Sciences at Subex started the talk with his journey in Subex. He explained the definition of Explainable AI and why it is the importance of using explainable AI, the taxonomy of interpretability that includes pre-modelling explainability, in-modelling explainability and post-modelling explainability, the difference between interpretability and completeness trade-off, the difference between interpretability and accuracy trade-off, among others. He further discussed Dominance analysis and how it is similar to Shapley approach but the latter has additional features.  

How to Use Predictive Analytics in Cricket

In this talk, Netali Agrawal, Lead Business Analyst at Infosys talked about a predictive analytics model in cricket where the goal of this model is to predict the winner for ICC men world cup 2019 based on the historical match data player-wise. She started from the problem statement and depicted the steps that took place in the model including feature engineering, data preparation, prediction on World Cup dataset, validation, among others. During the talk, Netali showed how she calculated the team strength based on the individual player batting and bowling strength who played in respective matches. 

Production Machine Learning & MLOps

Lavi Nigam, Data Scientist at Gartner talked about the difference between the current state of machine learning pipeline and new-age machine learning pipeline. Lavi shed light on the popular Machine Learning pipeline by Microsoft and explained that at the current scenario, developers talk mostly about the model development rather than the deployment. Lavi also pointed out that the current generation most stresses on the Data Science and algorithm part rather than the engineering part of machine learning and artificial intelligence.

A Black-Box Approach to Data Science to Focus on What Really Matters to the Business

In this talk, Gianluca Gindro, Head of Data Science at Kuoni discussed the importance of managing a black box and how to manage a black box from the business point of view. Treating data science as a ‘black-box’, the speaker focused on the key contact points of data science with the business that should never be neglected and also in practice how the same machine learning model can take different shapes depending on changing business needs.

A Glance from the Knowledge Talks

Developing a Product Centric, AI Driven Blueprint for the Enterprise

Johnson Poh, Head, Group Enterprise AI at UOB Bank discussed the essentials of artificial intelligence and its role in this new paradigm. In this talk, Poh covered several fundamental topics including AI, Big Data, Analytics and its broad field with the help of a Venn diagram, the relevance of emerging technologies, how to implement a data-driven strategy taking on the lens of people, process and technology, how AI changed the financial industry, among others.

Leveraging Data & Analytics for Social Goodness 

In this talk, Anirban Nandi, Head of Analytics at Rakuten covered how can data sciences help solve some of the pertinent problems of the society and seek help from fellow professionals to contribute to this cause as well. Anirban mentioned some of the available data sources including social media, mobile, biometric, satellite images, etc. and explained Multiple indicator cluster survey by UNICEF and how MICS plays a central role in the new 2030 agenda for Sustainable Development data landscape. 

My Experiences with Managing/Modeling/Analysing Data for Fast Growth

Nikola Sucevic, Head of Advanced Analytics at Smartfren PT talked about R&D efforts that exist on operator sides nowadays and how to manage teams of talented data scientists. He discussed how to model the future for real-time strategic decisions for investors and decision-makers in the telecom industry He showed a demo on planning board where he discussed the churn rates, growth rates, customer churn variations, and other such. 

Artificial Intelligence Essentials for Business Leaders

In this talk, Bhagirath Kumar Lader, Chief Manager, Business information System at GAIL discussed the essentials of AI, deep learning and machine learning, how to distinguish between the hype and reality, applications of AI in business, among others. Bhagirath explained the modern Analytics journey that includes descriptive analytics, diagnostic analytics, predictive analytics, etc. as well as the wall of analytics that needs to be broken through prescriptive and predictive analytics.  

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Impact of Data on Bringing Efficiencies in Logistics

Vikram Khurana, Head of Analytics and Business Intelligence at Delhivery talked about the abstraction of problems to run a logistics business and explored some of the analytics case studies in logistics which are helping an organization in this modern era of data. Vikram explained that most of the solutions in the logistics industry are defined around 3 important variables that are space, location and time as well as discussed some use cases on network design and projections.

Role of Data Strategy in Data Science and AI initiatives 

In this talk, Sateesh Rai, Head-Analytics at Orient Electric talked about the importance of data in an organisation. Sateesh explained the components of data strategy and depicted that CXOs need to understand why and how a data strategy would make a difference, how data was created and used. He discussed the various challenges in the organisational growth and business strategy that include lack of a clearly articulated business strategy, lack of cross-business, lack of priority, etc. and how business strategy comes first than data strategy.  

The Artificial Intelligence as a Service (AIaaS) Opportunity

Anish Agarwal, Director- Data & Analytics at RBS India talked about a number of topics related to Artificial Intelligence as a Service or AIaaS including benefits, importance, applications, among others. He discussed how this service model is aspiring to become just as widely adopted based on its potential to drive business outcomes with unmatched efficiency, how AIaaS can serve customers better and how this platform allows individuals and companies to experiment with AI for various purposes without large initial investment and with lower risk.

Cognitive Digital AI Platform for Telecom

In this talk, Sanjeev Chaube, EVP & Head-Big Data & Advanced Analytics at Vodafone Idea discussed how to improve the customer experience and increase profitability in telecom using Data Science, AI & Advanced Analytics Technologies. Sanjeev started the talk explaining the telecom market, how telecom as horizontal supports multiple domains including hospitals, airport, retail, etc., what is cognitive digital AI platform intuition, how to derive actionable insights and other such.

Role of Data & AI in Customer Centricity

Vijay Balakrishnan, Group Chief Fata Officer at Michelin talked about Customer Centricity and how it has become the heart of many organisations globally. He discussed the capabilities of a customer-centric organisation that includes understanding unique problems, the context of needs and delivering consistent and explained that a customer-centric organisation must-have features like building customer empathy into processes and policy, delivering value across customer’s lives, motivating employees to stay engaged and much more.  

Digital Fluency: Creating a Data-Driven Organization

In this talk, Michael Ferrari, Global Head of Climate & Agronomic Decision Sciences at Syngenta explained topics like quantamental that is a fusion of fundamental and quantum, digital fluency and hoe data science is related to digital fluency. He discussed how the notion of the ‘one size fits all’ data scientist has evolved to be a fictitious character, the benefits of focusing on Beta instead of Alpha, and the importance of domain expertise for data science to continue to evolve and provide value to organisations.

Data Literacy — It is not a Math Skill. It is a Life Skill

The last talk of the day was concluded by Kirk Borne, one of the top AI influencers and Principal Data Scientist at Booz Allen Hamilton. In this talk, Kirk discussed the meaning of data literacy and how it is more than just numbers and measurement of things, the complexity of big data. He further discussed on various important topics that are related to data and people often overlook or misunderstand the terms such as data awareness, data relevance, data literacy, data science and data imperative. 

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