AI Machine Learning 101 introductory presentation Understanding Machine Learning in 30 minutes for operational purposes such as building use cases, business impacts and possibilities for business improvements

1. Predictive Layer “Keep It Simple Series” Kiss 2018
“Machine Learning”
A series of 10 episodes
Credits /need to thank :
Andew Ng – Standford class of Machine Learning
Eric Grimson - MIT Class Machine Learning
PredictiveLayers Gurus

2. Arthur Samuel's definition from 1959:
Machine Learning: Field of study that gives
computers the ability to learn without being
explicitly programmed
Cognitive Computing
Keep It Simple Smart - Machine Learning #1/10

3. Tom Mitchell’s definition in 1998:
Well posed Learning Problem: A computer
program is said to learn from experience E with
respect to some task T and some performance
measure P, if its performance on T, as measured
by P, improves with experience E.
Cognitive Computing
Keep It Simple Smart - Machine Learning #2/10

4. Keep It Simple Smart - Machine Learning #3/10
The magic of Machine Learning :
generate programs based on data
that enable a totally adaptive set of
business applications that can serve
a truly agile business strategy.
In a way, Machine Learning generates
on a real time basis a new component
of your IS based on internal and
external data without depending on
massive complex expensive software
development or configuration.
It is a major game changer for
business
Credits /need to thank: Eric Grimson - MIT Class Machine Learning
Traditional Programming
Machine Learning
Program
Data
OutPut
Big Data
Program
Computing
Platform
OutPut
Computing
Platform

5. Keep It Simple Smart - Machine Learning #4/10

6. Mega Trend For The Next 10 Years:
COGNIFICATION OF BUSINESS
NEXT(X) = X + AI*
(*) AI: Artificial Intelligence , Machine Learning, Deep Learning
(*) X: Anything related to business performance, issue, challenge or process
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7. FUTURE OF BUSINESS
=
CURRENT + USE CASE (ARTIFICIAL INTELLIGENCE*)
(*) AI: Artificial Intelligence , Machine Learning, Deep Learning (mostly for image and language)
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SAMPLE BUSINESS USE CASES (MACHINE LEARNING)
Dynamic Demand Planning Dynamic Forecasting / Forecast to plan
Dynamic Pricing (Prescriptive) Dynamic Customer Segmentation
Predictive Maintenance (Prescriptive) Predictive Usage of Resources & Assets
Predictive Trafic for people, passengers or vehicles Prescriptive Workforce planning
Risk Management Credit Scoring

8. Keep It Simple Smart - Machine Learning #7/10
Select the right use case that creates value!
Align use case with Company Strategy and Purpose…
Value created should then become « obvious »
« Best Price For our Us and our Client » Dynamic Pricing (B2B and B2C)
« No queing for eating » Demand Planning & Forecasting
« The right product at the right place »
« No down time » Predictive Maintenance
« Less Trade & Promotion » Dynamic Forecasting and prescriptive A&P

9. TEAM of ARTIFICIAL INTELLIGENCE
PEOPLE & MACHINE LEARNING
CREATIVE Thinking PRODUCTIVE
DECISION Making EFFICIENT
Quality Time Time pressure
BEST TEAM
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10. AI Positive Loop
AI/ML
Product
Users
Initial Data Set
Defendable Business Position With unique
data assets initially build with MVP.
Then expand with users (Data
Accumulation as a core Capability), and
use cases.
Big data & Open Data with AI/ML become a
critical differentiator for the enterprise
More
data
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Using AI for sustainable business differentiation
Value
MVP (Minimum Viable Product)AI/ML: Artifcial Intelligence & Machine Learning

11. After the industrial revolution of artificial physical power
that is evolving dramatically with the shift from fossile to
renewable energy
Time has come to expand with the revolution of artificial
intelligence and brain power that will disrupt business
and society
THE TIME IS NOW !
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12. Credits /need to thank :
Andew Ng – Standford class of Machine Learning
Eric Grimson - MIT Class Machine Learning
PredictiveLayers Gurus
Predictive Layer “Keep It Simple Series” Kiss 2018
“Machine Learning”
A series of 10 episodes
Thank You