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The repository contains a portfolio of projects (jupyter notebooks) in the field of data science covering varied subjects like data analytics, data visualization and machine learning.

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jkoyan/datascience_reference

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datascience_reference

The repository contains the following directories:

  • data-analysis:

    • Contains projects that illustrate how to analyze a dataset using the python pandas framework.
  • data-visualization:

    • Contains sub directories that contain jupyter notebook files that illustrate the use of plotting tools to explore and visualize the data.
  • linear regression:

    • The jupyter notebook walks through the basics of the equation of a line and articulates the notion of using regression to predict the dependent variable using linear regression.
  • statistics:

    • The jupyter notebooks in this directory articulates the concept of univariate and bivariate statistics, a separate notebook delves into Standard Deviation.
  • machine-learning: The directory contains multiple sub directories, each for a type of machine-learning algorithm\concept.

    • k-nearest-neghbors: Contains a jupyter notebook that covers the K Nearest Algorithm, Train-Test validation and Cross validation using the scikit library.

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The repository contains a portfolio of projects (jupyter notebooks) in the field of data science covering varied subjects like data analytics, data visualization and machine learning.

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