Primer on Data Characteristics for Machine Learning For Non-Technicals

Mar 30, 20220 likes67 views

This document provides an overview of data characteristics, measurements, and analysis. It discusses key topics such as data quality, types of data including categorical and skewed data, big data sources like audio and video, and different types of data analysis including descriptive, exploratory, inferential, predictive, and causal analysis. The document emphasizes using data to tell stories and provides contact information for asking questions.

Primer On
Data Characteristics & Measurements
Puneet Arora
Ecologic Corporation

About Me
linkedin.com/in/puneetarora2000/
ASK Questions ON
twitter.com/puneetarora2000

Topic Covered:
What is Quality of Data ?
What is the meaning of Characteristics of Data ?
What is Metrics, Measurement ?
What is Big Data ?
What is Data Fusion ?
What is Data Argumentation ?
Types of AI
Issues in AI & Machine Learning
AI based Decision Making & Judgement

Quality of Data
Accuracy and
Precision
Legitimacy &
Validity
Reliability &
Consistency
Timeliness &
Relevance
Completeness &
Comprehensiveness
Availability &
Accessibility
OwnerShip
Granularity &
Uniqueness
ASK Questions ON
twitter.com/puneetarora2000

Types
ASK Questions ON
twitter.com/puneetarora2000

Shape of Data
Symmetric
Data
Asymmetric
Data /Skewed
Data
ASK Questions ON
twitter.com/puneetarora2000

Long & Short Tail
Long
Short
ASK Questions ON
twitter.com/puneetarora2000

Primer on Data Characteristics for Machine Learning For Non-Technicals

Types of Categorical Data
Ordinal e.g
Rank ,
Score

Data
Audio
Video
Sensor
ASK Questions ON
twitter.com/puneetarora2000

Data
Social
Economic
Political Data
ASK Questions ON
twitter.com/puneetarora2000

Measurements of Data
= Stories = Message,
Eliminate clutter
ASK Questions ON
twitter.com/puneetarora2000

Data Measurement & Analysis
Descriptive Exploratory Inferential
Mechanistic Causal
Predictive
ASK Questions ON
twitter.com/puneetarora2000

Explorative Analysis = Find Insights =
Interesting Variables
Mean , Mode, Median, Standard Deviation + Factor Analysis + Variate
Analysis
EDA explores data to find relationships between measures that tells us they exist, without the cause.
They can be used to formulate hypotheses.
Write Travel Journal

Descriptive Analysis = Explanation
Mean , Mode, Median, Standard Deviation,Skewness
Explanation = Story
What to measure
ASK Questions ON
twitter.com/puneetarora2000

Inferential Analysis = Guesswork
from Small Data
Distribution Shape,Variability,Skewness, Average, Factors
Tell about your Intelligent Guess
(conclusion) and intuition
(Prediction) from Data
ASK Questions ON
twitter.com/puneetarora2000

Predictive Analysis = History Analysis
Time series analysis, Regression
Use History to Tell Future
ASK Questions ON
twitter.com/puneetarora2000

Causal Analysis = Find root of the
problem ,but don’t blame
Correlation Analysis , Factor Analysis , Fish Bone Diagram
Find Cause , Write about ‘Effect’
ASK Questions ON
twitter.com/puneetarora2000

Mechanistic Analysis = Find Changes
Applied in physical or engineering sciences, situations that require
high precision and little room for error(only noise in data is
measurement error)
Designed to understand a biological or behavioral process, the
pathophysiology of a disease, or the mechanism of action of an
intervention.
ASK Questions ON
twitter.com/puneetarora2000

Digital Sociology | Political Science
Analysis of Digital Societies
Speed of Information = Information Communication Theory
Degree of Trust = Graph Theory {incidence and degree }
ASK Questions ON
twitter.com/puneetarora2000

Estimate , Analysis , Modelling
Simulate or Just Measure ?
Model History
Analysis Present
Simulate Future
ASK Questions ON
twitter.com/puneetarora2000

Estimate , Analysis , Modelling
Simulate or Just Measure ?
Monte Carlo
Simulators
ASK Questions ON
twitter.com/puneetarora2000

Don’t Forget
to Tell Data
Stories
Attention = Data Measured
ASK Questions ON
twitter.com/puneetarora2000

Thanks , Questions Please
You can Post Your Questions , Doubts Later On
https://twitter.com/puneetarora2000

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Primer on Data Characteristics for Machine Learning For Non-Technicals

1. Primer On Data Characteristics & Measurements Puneet Arora Ecologic Corporation

2. About Me linkedin.com/in/puneetarora2000/ ASK Questions ON twitter.com/puneetarora2000

3. Topic Covered: What is Quality of Data ? What is the meaning of Characteristics of Data ? What is Metrics, Measurement ? What is Big Data ? What is Data Fusion ? What is Data Argumentation ? Types of AI Issues in AI & Machine Learning AI based Decision Making & Judgement

4. Data

5. Quality of Data Accuracy and Precision Legitimacy & Validity Reliability & Consistency Timeliness & Relevance Completeness & Comprehensiveness Availability & Accessibility OwnerShip Granularity & Uniqueness ASK Questions ON twitter.com/puneetarora2000

6. Types ASK Questions ON twitter.com/puneetarora2000

7. Shape of Data Symmetric Data Asymmetric Data /Skewed Data ASK Questions ON twitter.com/puneetarora2000

8. Long & Short Tail Long Short ASK Questions ON twitter.com/puneetarora2000

10. Categorical Data Cats Dogs Elephants

11. Types of Categorical Data Ordinal e.g Rank , Score

12. BigData

13. Data Audio Video Sensor ASK Questions ON twitter.com/puneetarora2000

14. Data Social Economic Political Data ASK Questions ON twitter.com/puneetarora2000

15. Measurements of Data = Stories = Message, Eliminate clutter ASK Questions ON twitter.com/puneetarora2000

16. Data Measurement & Analysis Descriptive Exploratory Inferential Mechanistic Causal Predictive ASK Questions ON twitter.com/puneetarora2000

17. Explorative Analysis = Find Insights = Interesting Variables Mean , Mode, Median, Standard Deviation + Factor Analysis + Variate Analysis EDA explores data to find relationships between measures that tells us they exist, without the cause. They can be used to formulate hypotheses. Write Travel Journal

18. Descriptive Analysis = Explanation Mean , Mode, Median, Standard Deviation,Skewness Explanation = Story What to measure ASK Questions ON twitter.com/puneetarora2000

19. Inferential Analysis = Guesswork from Small Data Distribution Shape,Variability,Skewness, Average, Factors Tell about your Intelligent Guess (conclusion) and intuition (Prediction) from Data ASK Questions ON twitter.com/puneetarora2000

20. Predictive Analysis = History Analysis Time series analysis, Regression Use History to Tell Future ASK Questions ON twitter.com/puneetarora2000

21. Causal Analysis = Find root of the problem ,but don’t blame Correlation Analysis , Factor Analysis , Fish Bone Diagram Find Cause , Write about ‘Effect’ ASK Questions ON twitter.com/puneetarora2000

22. Mechanistic Analysis = Find Changes Applied in physical or engineering sciences, situations that require high precision and little room for error(only noise in data is measurement error) Designed to understand a biological or behavioral process, the pathophysiology of a disease, or the mechanism of action of an intervention. ASK Questions ON twitter.com/puneetarora2000

23. Digital Sociology | Political Science Analysis of Digital Societies Speed of Information = Information Communication Theory Degree of Trust = Graph Theory {incidence and degree } ASK Questions ON twitter.com/puneetarora2000

24. Estimate , Analysis , Modelling Simulate or Just Measure ? Model History Analysis Present Simulate Future ASK Questions ON twitter.com/puneetarora2000

25. Estimate , Analysis , Modelling Simulate or Just Measure ? Monte Carlo Simulators ASK Questions ON twitter.com/puneetarora2000

26. Don’t Forget to Tell Data Stories Attention = Data Measured ASK Questions ON twitter.com/puneetarora2000

27. Thanks , Questions Please You can Post Your Questions , Doubts Later On https://twitter.com/puneetarora2000

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