Basics of data

1. AI Club

2. AI Club
The Basics of
Data

3. The Basics of
Data
Columns
Rows

4. The Basics of Data
Columns
Rows
Sample
Each row is an Example for
the AI to Train with
Feature Label

5. The Basics of Data
Features Labels
Features can come in many types
(numbers, categories, text etc.)
Common real life examples take 100s
to 1000s of features!
Each dataset has
only one Label
column
Samples
Each row is an
Example for
the AI to Train
with
Number of
Countries Visited
Number of Years
in School
Height
(Feet)
Who am I?
20 15 5.2 Adult
2 3 3.5 Child
10 12 4.9 Adult

6. The basics
of AI
Training: Use data to
develop a ML model

7. Example: Use AI to Guess a Person’s Mood
Training: Use text data
describing feelings for happy or
sad. Develop a model.
Examples of
happy and sad

8. Example: Use AI to Guess a Person’s Mood
Training: Use text data
describing feelings for happy or
sad. Develop a model.
Examples of
happy and sad
Question ‘sentence’ This is called a feature
Answers ‘feeling’ This is called a label

9. AI Basics

10. AI Basics
Training : Use data to develop a ML model.
Model : A formula learned from the data
that can be used to predict new outcomes.
Inference/Prediction : Using the model
to answer new questions.

11. Training : Use data on feelings for happy or
sad. Develop a model
Model : Learn how to map feelings to
“Happy” or “Sad”
Inference/Prediction : Provide a new
feeling “example – I am feeling great!”.
Predict that this is “Happy”
Example: Use AI to Guess a Person’s Mood

12. What is an AI Service?

13. What is an AI Service?
• An AI Service is a program that
takes questions (new data) and
uses a model to create answers
(predictions)

14. What is an AI Service?
• An AI Service is a program that
takes questions (new data) and
uses a model to create answers
(predictions)
• An AI service connects with your
application
• Application sends questions
• AI service sends back
predictions/answers
Application uses the answers

15. What is an AI Service?
• An AI Service is a program that
takes questions (new data) and
uses a model to create answers
(predictions)
• An AI service connects with your
application
• Application sends questions
• AI service sends back
predictions/answers
Application uses the answers

16. THANK YOU
https://aiclub.world
info@pyxeda.ai