This document discusses the relationship between artificial intelligence (AI) and big data. It defines both AI and big data. AI is making computers do intelligent tasks like humans, while big data refers to large amounts of structured and unstructured data. The document explains that AI needs large amounts of data to replicate human intelligence and make intelligent decisions, just as human intelligence is built on experiences and data. It provides examples of how AI uses big data, such as Google's self-driving cars gathering sensor data to make driving decisions. The document also covers predictive analytics, unstructured data analysis, and data mining techniques like genetic algorithms and fuzzy logic.

2. and
Part - 2

3. Group Members
Member’s Name Member’s ID
Md. Mehedi Hasan 132-15-2629
Mohammad Abdul Kaiyum 132-15-2713
Maruf Abdullah 132-15-2703
Rajib Chandra Das 132-15-2747
Rakibul Islam 132-15-2770

4. At a Glance
Page#
What is Big Data?? 05
What is AI?? 06
Relationship between AI & Big Data 07 – 09
Predictive Data Analytics & Big Data 10 – 13
Unstructured Data Analytics 14 – 16
Data Mining using GAs 17 – 18
Data Mining using Fuzzy Logic 19 – 20
Why AI & Big Data need each other?? 21 – 22
Live Example of Relationship 23 – 14
References 25

5. What is Big Data??
We already told about big data in our previous
discussion. For your attention we want to tell
that again.
Big data equals to big deals. A lot of numbers
of data may be structured or unstructured.
For this time just keep this words in mind.
Later of the discussion we will discuss on it
briefly.
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6. What is AI??
Artificial Intelligence is the science of making
computers do things that require intelligence
when done by humans. All AI designs are at
least somewhat inspired by the human brain.
The objective of AI is to build intelligent
agents. For example, consider video game
characters. When a video game character
goes from point A to point B, there is AI
algorithm called path finding.
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7. Relationship Between AI & Big Data
Human intelligence builds up on what we
read, observe, learn, sense and experience.
It's our ability to store large amount of data,
accumulated over years and co-relating a
few data points to answer a certain
question, that makes us intelligent.
Similarly for machines to replicate human
intelligence, they'll need to absorb large
amount of data to make an intelligent
decision.
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8. Relationship Between AI & Big Data
Google's self driving cars gather large
amount of data by monitoring surrounding
environment through an array of sensors like
infrared cameras, proximity sensors etc…
The machine driving the car & co-related
information gathered from this large amount
of data to make an intelligent decision.
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9. Relationship Between AI & Big Data
09

10. Predictive Data Analytics
Predictive analytics is the practice of
extracting information from existing data
sets in order to determine patterns and
predict future outcomes and trends.
Predictive analytics does not tell you what
will happen in the future. It forecasts what
might happen in the future with an
acceptable level of reliability, and includes
what-if scenarios and risk assessment.
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11. Predictive Data Analytics
Predictive data analytics is essential if you
want to know what consumers are thinking
and what they are likely to respond to
positively. This also ties in with big data and
how to use it to best effect. The answer lies
in using narrow AI to track consumer
sentiment, and separately extract specific
relevant information from big data.
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12. Predictive Data Analytics Value Chain
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13. Predictive Data Analytics
Businesses collect vast amounts of real-time
customer data and predictive analytics uses
this historical data, combined with customer
insight, to predict future events. Predictive
analytics enable organizations to use big data
to move from a historical view to a forward-
looking perspective of the customer.
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14. Unstructured Data Analytics
Unstructured data is a generic label for describing
data that is not contained in a database or some
other type of data structure. Unstructured data can
be textual or non-textual. Textual unstructured data
is generated in media like email messages,
PowerPoint presentations, Word documents,
collaboration software and instant messages. Non-
textual unstructured data is generated in media like
JPEG images, MP3 audio files and Flash video files.
To discovery meaningful data from text, speech,
videos, images etc…
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15. Unstructured Data Analytics
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16. Unstructured Data Analytics
There are few data mining techniques
including traditional data mining, genetic
algorithms, fuzzy logic etc...
In short we will discuss about data mining
using genetic algorithms and fuzzy logic
techniques.
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17. Data Mining using Genetic Algorithm
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Genetic algorithm is one of the commonly used
approaches on data mining.
Data mining has a goal to extract knowledge from
large databases. To extract this knowledge, database
may be considered as large search space and mining
algorithm as a search strategy. In general, a search
space consists of an huge number of elements to
make an extensive search. Therefore, efficient search
strategies are of vital importance. Search strategies
based on genetic algorithms have been applied
successfully in a wide range of applications.

18. Data Mining using Genetic Algorithm
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19. Data Mining using Fuzzy Logic
19
Fuzzy logic is a computer-based logic that is
focused on uncovering “degrees of truth”
or “partial truths” rather than targeting the
truth itself. Because of this it’s sometimes
called many valued logic.
In Big Data analysis, and specifically the
Smart Data analysis that we undertake,
fuzzy logic is one of the key tools in
uncovering truth.

20. Data Mining using Fuzzy Logic
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21. Why AI & Big Data Need each other??
21
If you’re collecting & analyzing customer information,
gleaning insights into what customers want and need,
and acting on those insights. Then you may able to
position products to respond to customers’ greatest
needs & you know it’s working, because you’re collecting
data that proves it. You’re way ahead of most of your
peers in deriving real value from big data. But you’re not
done yet.
If you want to stay competitive then you have to do much
more to get the maximum value from the customer data
you’re collecting and to do it, you need artificial
intelligence.

22. Why AI & Big Data Need each other??
22
AI needs to research on market & competitors.

23. Example of Relationship between AI & Big
Data
23
At the moment of ending our discussion we
want to say another live example of
relationship between AI & Big Data. That’s ….
Google Translate can be used online for free
by anyone to translate text back in more than
70 languages. This statistical translator uses
billions of word sequences and correlative
algorithms.

24. Live Example of Relationship
between AI & Big Data
24
Here to convert English to Chinese Google uses
correlative algorithms (works as AI) and a huge
database of words of both English & Chinese.

25. References & Information
Sources
 Google & Google Image Search
 Quora
 Slide-share
 Forbes
 YouTube
 www.automated-intelligence.com
 www.ai-one.com
 www.webopedia.com
 https://www.uic.edu (PDF)
 http://www.aaai.org/ (PDF)
 www.researchgate.net and few more ……….
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