The document discusses the basics of machine learning, emphasizing the importance of data management, feature engineering, and model training. It highlights that proper data preprocessing and thoughtful training processes are crucial to avoiding overfitting and bias in machine learning algorithms. The speaker, Demetris Trihinas, stresses the need for human oversight in generating insights from ML models.

1. 5/22/19 1Demetris Trihinas
trihinas.d@unic.ac.cy
1ACCA ML Panel| Nicosia, May 2019
Department of
Computer Science
Machine Learning
Panel Opening Comments
Demetris Trihinas
Department of Computer Science
AILab @ University of Nicosia
trihinas.d@unic.ac.cy

2. 5/22/19 2Demetris Trihinas
trihinas.d@unic.ac.cy
2ACCA ML Panel| Nicosia, May 2019
Department of
Computer Science
Full-Time Faculty Member
University of Nicosia
“Designing and developing scalable and self-adaptive tools for data
management, exploration and visualization”
@dtrihinas
http://dtrihinas.info
https://ailab.unic.ac.cy/https://www.slideshare.net/DemetrisTrihinas

3. 5/22/19 3Demetris Trihinas
trihinas.d@unic.ac.cy
3ACCA ML Panel| Nicosia, May 2019
Department of
Computer Science
What is NOT Machine Learning
• Any question you can ask and get an –immediate and
concrete– answer (e.g., database, spreadsheet).
• How many sofas models are currently in stock?
• How many sofas did we sell in Germany last month?
• Which of our customers bought a sofa worth more than 500
euros this quarter?

4. 5/22/19 4Demetris Trihinas
trihinas.d@unic.ac.cy
4ACCA ML Panel| Nicosia, May 2019
Department of
Computer Science
The Machine Learning Process
Data and
Labels
Feature
Engineering
ML
Algorithm
Bike
Car
Bike
< 2, 170, 35, 169, 51, 38, …>
< 2, 119, 28, 210, 52, 02, …>
Car
<4, 13, 157, 90, 178, 145, …>
<4, 12, 170, 82, 193, 145, …>
wheels
Training
Testing
Data
Feature
Engineering
Inferencing
Statistical
Model
<4, 18, 200, 64, 170, 141, …> It’s a… Car
Finding ”patterns” from features
! = #(%, ')

5. 5/22/19 5Demetris Trihinas
trihinas.d@unic.ac.cy
5ACCA ML Panel| Nicosia, May 2019
Department of
Computer Science
ML Modeling is an Approximation...
Feature
Engineering
ML
Algorithm
Training
Testing
Data
Feature
Engineering
Statistical
Model
<4, 18, 200, 64, 170, 141, …>
<3, 22, 23, 31, 101, 205, …>
Data and
Labels
Inferencing
It’s a Car I’m 0.88 sure
It’s a Car I’m 0.71 sure

6. 5/22/19 6Demetris Trihinas
trihinas.d@unic.ac.cy
6ACCA ML Panel| Nicosia, May 2019
Department of
Computer Science
It’s Also Called “Learning” Because…
Feature
Engineering
ML
Algorithm
Training
Testing
Data
Feature
Engineering
Statistical
Model
<4, 18, 200, 64, 170, 141, …> It’s a… Car, 0.88
<3, 22, 23, 31, 101, 205, …> It’s a… Car, 0.71
<3, 22, 23, 31, 101, 205, …> It’s a… tricycle, 0.93
Data and
Labels
Evaluate
and
RetrainInferencing

7. 5/22/19 7Demetris Trihinas
trihinas.d@unic.ac.cy
7ACCA ML Panel| Nicosia, May 2019
Department of
Computer Science
How Do Robots See Us

8. 5/22/19 8Demetris Trihinas
trihinas.d@unic.ac.cy
8ACCA ML Panel| Nicosia, May 2019
Department of
Computer Science
Training is of Utmost Importance
• More training data is good but too much leads to overfitting
(irrelevant details are modeled).
• Algorithms are not racist, do not hold prejudice or apply
stereotypes… yes, but what happened to Amazon?
Memorizing the answers is NOT Learning

9. 5/22/19 9Demetris Trihinas
trihinas.d@unic.ac.cy
9ACCA ML Panel| Nicosia, May 2019
Department of
Computer Science
Beware of the “Trainer”…
https://www.businessinsider.com/amazon-built-ai-to-hire-people-discriminated-against-women-2018-10

10. 5/22/19 10Demetris Trihinas
trihinas.d@unic.ac.cy
10ACCA ML Panel| Nicosia, May 2019
Department of
Computer Science
Data Preprocessing
• Preprocessing significantly increases ML performance
and result quality.
• Is 1% more error tolerable if computation “promises”
to run for 10min instead of 5 hours?
• Data Reduction –remove
insignificant model dimensions.
• Data Cleaning –remove
incomplete and “dirty” data.
Do not “influence” result

11. 5/22/19 11Demetris Trihinas
trihinas.d@unic.ac.cy
11ACCA ML Panel| Nicosia, May 2019
Department of
Computer Science
What is YOUR Role?
• Ask good questions – a model is based on a hypothesis.
• Provide training data – BEWARE training can lead to bias.
• Assess the quality of results – retrain let the model “learn”.
• TEST, TEST and TEST again.
The Ability Matrix
Insights are generated
by humans not
machines!

12. 5/22/19 12Demetris Trihinas
trihinas.d@unic.ac.cy
12ACCA ML Panel| Nicosia, May 2019
Department of
Computer Science
Questions?
Demetris Trihinas
Department of Computer Science
AILab @ University of Nicosia
trihinas.d@unic.ac.cy