Analytics and Machine Learning - How Can Analytics and Data Science Leverage Machine Learning in Future?
Autor: Ankita Jena • February 9, 2017 • Dissertation • 2,743 Words (11 Pages) • 1,001 Views
CRISIL YOUNG THOUGHT LEADER
COMPETITION
Analytics and machine learning: How can analytics and data science leverage machine learning in future?
ANKITA JENA
INDIAN INSTITUTE OF MANAGEMENT INDORE
PGP (2015- 2017)
Email: p15ankitaj@iimidr.ac.in
Index
- Introduction
- What is Machine Learning?
- Basic Definition
- Different Types of Machine Learning
- Benefits of using Machine Learning with Analytics
- Machine Learning Market Size and Trends
- Machine Learning Leveraging Analytics
- Challenges in adoption of Machine Learning and analytics
- Growth of Machine Learning with Analytics
- Growth opportunities for Machine Learning
- Machine Learning in Manufacturing
- Machine Learning in Retail
- Machine Learning in Health care and Living
- Machine Learning in Financial Services
- Future of Machine Learning
- Conclusion
Introduction
“Numbers have an important story to tell. They rely on you to give them a voice.” – Stephen Few
As you read the first few lines of this thesis, nearly 2.5 million comments have been posted on Facebook, some 200 million mails have been sent by Gmail, 300,000 tweets were just made. We know that 90% of the data today has been generated in the last 2 years, 2.5 million quintillions of data is being created everyday and by 2018, we will be talking about 50,000 GB of data per second. When we talk about Big Data, we often talk about these numbers. But these are just numbers. What we often miss is with every comment, every tweet, every photo upload there is a story that is being told. That is exactly what Stephen Few meant when he said the above line.
This explosion of data has set forth a world of information waiting to be mined, which cannot be tamed with rules. The programs and algorithms which were used uptil now have a fixed set of rules that fail to discover the true story. Analytics and Machine Learning thus herald an era of discovering insights from heaps of Big Data. As the data grows and becomes more and more complex, it fosters Machine Learning and needs it as well. Machine Learning is a revolution in the lines of introduction of personal computers and Internet, if not bigger.
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