This book covers research work spanning the breadth of ventures, a variety of challenges and the finest of techniques used to address data and analytics, by subject matter experts from the business world. The content of this book highlights the real-life business problems that are relevant to any industry and technology environment. This book helps us become a contributor to and accelerator of artificial intelligence, data science and analytics, deploy a structured life-cycle approach to data related issues, apply appropriate analytical tools & techniques to analyze data and deliver solutions with a difference. It also brings out the story-telling element in a compelling fashion using data and analytics. This prepares the readers to drive quantitative and qualitative outcomes and apply this mindset to various business actions in different domains such as energy, manufacturing, health care, BFSI, security, etc.
Chapter
1. Dynamic Demand Planning for Distorted Historical Data Due to
Pandemic.
Chapter
2. Cognitive Models to Predict Pipeline Leaks and
Ruptures.
Chapter
3. Network Optimization of the Electricity Grid to manage
Distributed Energy Resources using Data & Analytics.
Chapter
4. Enhancing
Market Agility Through Accurate Price Indicators using Contextualized Data
Analytics.
Chapter
5. Infrastructure for Automated Surface Damage
Classification and Detection in Production industries using ResUNet based
Deep Learning Architecture.
Chapter
6. Cardiac Arrhythmias Classification &
Detection for Medical Industry Using Wavelet Transformation & Probabilistic
Neural Network Architecture.
Chapter
7. Investor Behavior towards Mutual
Fund.
Chapter
8. iMask An Artificial Intelligence Based Redaction Engine.-
Chapter
9. Artificial Intelligence for Proactive Vulnerability Prediction and
interpretability using Occlusion.
Chapter
10. Intrusion Detection System
using Signature based Detection and Data Mining Technique.
Chapter
11. Cloud
Cost Intelligence using Machine Learning.
Chapter
12. Mining deeper Insights
using Unsupervised NLP.
Chapter
13. Explainable AI for ML OPS.
Neha Sharma is a data science crusader who advocates its application for achieving sustainable goals, solving societal, governmental and business problems as well as promotes the use of open data. She has more than 22 years of experience and presently working with Tata Consultancy Services and is a Founder Secretary, Society for Data Science. Prior to this she has worked as Director of premier Institute of Pune, that run post-graduation courses like MCA and MBA. She is an alumnus of a premier College of Engineering and Technology, Bhubaneshwar and completed her PhD from prestigious Indian Institute of Technology, Dhanbad. She is a Senior IEEE member, Secretary IEEE Pune Section and ACM Distinguished Speaker. She is an astute academician and has organized several national and international conferences and published several research papers. She is the recipient of Best PhD Thesis Award and Best Paper Presenter at International Conference Award at National Level. She is a well-known figure among the IT circle, and well sought over for her sound knowledge and professional skills. Neha Sharma has been instrumental in integrating teaching with the current needs of the Industry and steering students towards their bright future.
Mandar Bhatavdekar is working with Tata Consultancy Services as a Head of Center of Excellence for Analytics & Insights. He has vast experience of three decades, a Computer Engineering Graduate from VJTI, Mumbai. His focus areas include driving business and operational strategy, elevating the TCS brand in data, analytics and AI world, by bringing in thought leadership, improving our analyst positioning and customer mindshare. He comes with a rich multi-disciplinary experience within TCS from services to product development, sales to delivery, across diverse industries. He is a certified enterprise architect and has earlier led many crucial transformational engagements. On the personal front, he loves music, drama and poetry. He is a friendly face for most people who have been associated with him.
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