AI - Robbi

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    Using Data Mining

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    Branch of Computer science which deals with intelligence

    behavior, learning and adaptation in machines.

    Artificial Intelligence

    Man behind AI is John McCarthy

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    Artificial intelligence (AI)

    Computers with the ability to mimic or

    duplicate the functions of the human brain

    Artificial intelligence systems

    The people, procedures, hardware, software,

    data, and knowledge needed to developcomputer systems and machines that

    demonstrate the characteristics of intelligence

    Overview of AI

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    Intelligent behavior Learn from experience

    Apply knowledge acquired from experience

    Handle complex situations

    Solve problems when important information ismissing

    Determine what is important

    React quickly and correctly to a new situation

    Understand visual images Process and manipulate symbols

    Be creative and imaginative

    Use heuristics

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    Branches of AI

    Perceptive system

    A system that approximates the way a human sees,

    hears, and feels objects

    Vision system Capture, store, and manipulate visual images and

    pictures

    Robotics

    Mechanical and computer devices that performtedious tasks with high precision

    Expert system

    Stores knowledge and makes inferences

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    Learning system

    Computer changes how it functions or reacts to

    situations based on feedback

    Natural language processing

    Computers understand and react to statements and

    commands made in a natural language, such as

    English

    Neural network

    Computer system that can act like or simulate the

    functioning of the human brain

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    Artificialintelligence

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    Most Famous application of

    AI which is used in games,

    puzzles and battles

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    Use of Data Mining in Artificial Intelligence

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    Process of semi-automatically analyzing large

    databases to find patterns that are:

    valid: hold on new data with some certainity

    novel: non-obvious to the system

    useful: should be possible to act on the item

    understandable: humans should be able to

    interpret the pattern Also known as Knowledge Discovery in Databases

    (KDD)

    Data Mining

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    Credit ratings/targeted marketing: Given a database of 100,000 names, which persons are

    the least likely to default on their credit cards?

    Identify likely responders to sales promotions

    Fraud detection

    Which types of transactions are likely to be fraudulent,given the demographics and transactional history of aparticular customer?

    Customer relationship management: Which of my customers are likely to be the most loyal, and

    which are most likely to leave for a competitor? :

    Need of Data Mining

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    Basic Applications

    Banking: loan/credit card approval

    predict good customers based on old customers

    Customer relationship management:

    identify those who are likely to leave for a competitor.

    Targeted marketing:

    identify likely responders to promotions

    Fraud detection: telecommunications, financial transactions from an online stream of event identify fraudulent events

    Manufacturing and production:

    automatically adjust knobs when process parameterchanges

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    The US Government uses Data Mining to trackfraud

    A Supermarket becomes an information broker

    Basketball teams use it to track game strategy

    Cross Selling

    Target Marketing

    Holding on to Good Customers Weeding out Bad Customers

    AI along with DM

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    Three fundamental AI techniques used in Data Mining

    Knowledge Representation: Data Mining seeks to find out

    interesting patterns from large volumes of data.

    Knowledge Acquisition: The discovery process contains various

    algorithms and methods to analyze data.

    Knowledge Interference: The patterns discovered from data is to

    be verified by various applications.

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    Algorithm Mostly Used

    Apriori Algorithm

    Apriori is a classic algorithm for learning association rules.

    Apriori is designed to operate on databases containing

    Transactions.

    Apriori algorithm helps to find associations in the form of

    patterns which are very useful.

    Apriori uses a "bottom up" approach, breadth-first searchand a tree structure to count candidate item sets efficiently.

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    Applications of Apriori Algorithm

    It helps in finding out associations and placement of different

    products in a super market or a departmental store.

    It helps in determine the customer preference in a video store.

    It helps in detecting fraud over a series of transactions.

    Its applications are numerous and the list goes on

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    Certain methods Followed by AI in Data Mining

    Clustering

    Collaborative Filtering

    Categorical Data Filtering

    Association Filtering

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    Thank You