1. Major improvements in accuracy in speech recognition and image recognition opens up a new field in human computer interaction. With computers able to correctly interpret almost all interactions without direct contact with keyboard or mouse, a major data source has opened up for Data Scientists to explore.
2. A system which is 80% accurate may not usable, however, when accuracy crosses 95%, there is a major turnaround in large scale adoption.
3. Self driving cars will lead to major leaps in technologies for object recognition -> not just previously known objects, also to anticipate and correctly handle unexpected objects.
4. In my view, there are four key dimensions of Data science, these are Data, Domain Expertise, Machine learning algorithms and Technology of Deployment. Value creation is possible across all the dimensions of Data Science. Better quality data, higher volume of relevant and contextual data can create value, and domain expertise remains critical in making successful deployments of data science projects. Our focus on machine learning algorithms is important, however, value creation happens across all the four dimensions.
5. We have seen a 5X increase in jobs which require machine learning and neural networks expertise.
Data Science is now mainstream and it is important for every organization to invest in Data Science and benefit from it.
2. Data Continues to Explode – Volume,
Velocity and Variety
• Over 3.5 bn Smartphone users
– Each interaction is an
opportunity to improve the
next interaction for the user
– Both structured and
unstructured data is
generated on an ongoing basis
• Huge opportunity in interpreting
the data
– Each application by itself can
optimize the experience
– Aggregating data across
multiple application brings
interesting possibilities
3. Analytics is Changing the Face of This
World – Speech Recognition
• Interactive Natural Language Speech Recognition in
a general context – Siri
• Several new use cases open up across multiple
context
4. Analytics is Changing the Face of This
World – Self Driving Cars
• Self driving cars process real time traffic, route and
traffic signals with precision matching humans
• Streaming video, image processing and object
recognition at run time with almost negligible error
5. Analytics is Changing the Face of This
World – Healthcare
Deep Learning techniques have enabled major
improvements in Prediction Accuracy.
MRI Images and
detection of
abnormalities is
one problem that
has been the
focus of AI for
decades now.
6. Analytics is Changing the Face of This
World –Search
• From Personalization of
news to social network
data feeds
• From finding the most
relevant scientific
publication to finding the
most relevant learning
video
• From finding the most
relevant job on
Naukri.com to finding the
most relevant match on
Jeevansathi.com
7. Machine Learning Has
Great RoI -> Rush to Build
Data Science Teams
Better Customer
experience => $$ ↑
Data science is now
mainstream
Source of Competitive
Advantage
8. Four Pillars of Data Science and
Machine Learning
• New methods of
technology/
deployment can
generate superior
business benefits
• Use domain
understanding to
Introduce special
features/
experiments
• Machine Learnings
algorithms/ data
structures
• Enrich and expand
data sources
• Improve quality of
data
Data
Sources
Machine
Learning
Algorithm
Tech for
Deploying
Domain
Expertise
9. Data Scientist & Machine Learning Jobs ↑
• Data Scientist
• Natural Language Processing-
Technical Architect
• Adv. Statistical Modeling Professional
• Big Data Hadoop Developer /Architect
• Machine Learning Applied Engineer
• Product Manager- Search & Discovery
• Product Manager- Recommendations
• Consultant – Machine Learning
• #Jobs for Machine Learning and Data
Science in last 2 years – 5X ↑
10. Learning and Certifications
• Shortage of good
quality Data
Scientists
• Big Data and Data
Science courses
are very popular
• Certifications
from reputed
course providers
are valuable.