Subject Details
Dept     : CS-DA
Sem      : 3
Regul    : 2022-2025
Faculty : Ms Sangeetha k
phone  : NIL
E-mail  : sangeetha3mca@gmail.com
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  • Lecture Notes

    Dear Students the Lecture Notes has been uploaded for the following topics:
    Introductory Background,
    Big Data Architectures

  • Lecture Notes

    Dear Students the Lecture Notes has been uploaded for the following topics:
    Clustering- Distance Measures,
    Clustering- Distance Measures,
    Clustering Validation,
    Clustering Techniques,
    K-means,
    DBSCAN,
    Agglomerative Hierarchical Clustering Technique,
    Frequent Pattern Mining,
    Association Rules,
    Behind Support and Confidence,
    Other Types of Pattern.,
    FP-Growth,
    Regression - Predictive Performance Estimation,
    Finding the Parameters of the Model,
    Linear Regression,
    The Bias-variance Trade-off-Shrinkage Methods,
    Methods that use Linear Combinations of Attributes,
    Classification - Binary Classification,
    Predictive Performance Measures for Classification,
    Distance-based Learning Algorithms,
    Probabilistic Classification Algorithms

  • Lecture Notes

    Dear Students the Lecture Notes has been uploaded for the following topics:
    Additional Predictive Methods-Search-based Algorithms

  • Lecture Notes

    Dear Students the Lecture Notes has been uploaded for the following topics:
    Two Ordinal Attributes.

  • Lecture Notes

    Dear Students the Lecture Notes has been uploaded for the following topics:
    Descriptive Multivariate Analysis - Multivariate Frequencies,
    Multivariate Data Visualization,
    Infographics and Word Clouds,
    Data Quality and Preprocessing,
    Data Quality,
    Converting to a Different Scale Type,
    Data Transformation,
    Two Ordinal Attributes.

  • Assignment

    Assignment topic is Data Quality and Preprocessing and due date is .

  • Assignment

    Assignment topic is Descriptive Statistics and due date is .

  • Lecture Notes

    Dear Students the Lecture Notes has been uploaded for the following topics:
    Small Data -What is Data?,
    A Short Taxonomy of Data Analytics,
    Examples of Data Use,
    A Project on Data Analytics

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