This document discusses combining human learning and machine learning to improve recommendation solutions. It proposes starting with a heuristic human approach, then adding machine learning methods like scoring and feature selection over time. Multiple algorithms, both human learning and machine learning, would be tested alongside each other in a "King of the Hill" approach. The goal is to develop the best performing solution by leveraging both human knowledge and machine learning capabilities. Feedback would be used to refine the models on an ongoing basis.

1. RECOMMENDATION SOLUTION:
Combining
Human Learning & Machine Learning
1

2. 2
Uzi Blum
VP Business Intelligence & Analytics
Analytics
Data Driven Application

3. LAUNCH
your app and scale your user base
GROW
your app with quality users
RETAIN
your users and maximize your ROI
3
We deliver the right users at the right
time at every step of your app
marketing lifecycle

4. HUMAN LEARNING
4
Human learning is the act of
acquiring knowledge. It occurs
during training and personal
experience.
This knowledge resides in ones
brain.

5. 5
Can
Machine Learning
replace
Human Learning ?
vs.

6. HUMAN vs. MACHINE
6

7. Typical Human and Machine Learning Approach
7
Identify
Revenue
Potential
Implement
Recommendation
solution based on
heuristic
approach
Performance
Measuring
+
Internal
Feedback
(Human)
Adding scoring
and feature
selection
mechanism for
ML
Scaling à Direct
recommendation
to clients
“King of the Hill”
Multi algos HL
and ML and
HL+ML
MONTH 0 MONTH 1 MONTH 2 MONTH 3 MONTH 4 MONTH 5
“Similarity
Density”What are the
most attractive
products for
each client?
“ May the best Algo Win! “
Random Forest K-Means

8. Tim Maor Stefan
A
B
C
D
E
SIMILARITY DENSITY
8
PRODUCT
CLIENT
DENSITY
2/3
2/3
3/3
1/3
1/3
DENSITY 4/5 2/5 3/5

9. THE “RAINBOW” APPROACH
9
DEVELOPMENT
Problem
Data
Algo/s
Feedback &
Performance
Distribution
Method
Recommendation
List
OUTPUT

10. 10
KEY TAKE AWAYS
• Performance and Feedback
“What was the performance on the latest
recommendation?
• Business Impact
“How much impact did I make on the business
in the last month?”
• Velocity
“How fast can we create a minimal viable
product?”

11. Selected Partners:
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Questions?
uzi.blum@applift.com | www.AppLift.com