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Building a ML Model
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Building a ML Model

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  1. A-B_Testing A-B_Testing Public

    Comparing the lift in the subscription rate between the control and personalized contents across marketing channels, and conducting two sample t-test to determine if the difference is statistically…

    Jupyter Notebook 3 1

  2. Marketing-Campaign-Analysis Marketing-Campaign-Analysis Public

    Measuring the success of a marketing campaign with conversion and retention rates. Analyzing which marketing channel (email, Facebook, Instagram, direct mail) had the lowest cost-per-acquisition.

    Jupyter Notebook 2 5

  3. Mystery-Puzzle-Data Mystery-Puzzle-Data Public

    Cleaning and manipulating mystery data with Python’s Pandas library, and visualizing with matplotlib

    Jupyter Notebook

  4. Boxplots-Hypothesis-Testings-for-Fruit-Fly-Behaviour Boxplots-Hypothesis-Testings-for-Fruit-Fly-Behaviour Public

    Conducting one-factor analysis of variance and its assumptions (normality and homogeneity of variance) with R if two groups of data show statistically different behavior. Visualizing data with boxp…

    R

  5. Checking-Data-Quality Checking-Data-Quality Public

    Checking if data well-represents the natural behaviour of consumers

    R

  6. Algorithm-Newton-Raphson-Method Algorithm-Newton-Raphson-Method Public

    Applying Newton's method to approximate root values

    R