About Asel Mendis

I'm finishing my Masters Degree in Analytics in June 2019 with knowledge in Applied Statistics and Machine Learning using R, SAS, Jupyter Notebooks, SQL and Python for Data Science, Currently undertaking Data Warehouse Certification on Amazon Web Services Training and Educate. I undertake my own projects in my spare time and can be viewed in my blog https://easydsrp.com/. I write for the online publishers Medium and Towards Data Science on a freelance basis. I'm also seeking employment as well and am open to discuss any potential opportunities.

Asel Mendis Posts (6)

  • Naive Bayes: A Baseline Model for Machine Learning Classification Performance - 07 May 2019
    We can use Pandas to conduct Bayes Theorem and Scikitlearn to implement the Naive Bayes Algorithm. We take a step by step approach to understand Bayes and implementing the different options in Scikitlearn.
  • Gold BlogData Visualization in Python: Matplotlib vs Seaborn - 19 Apr 2019
    Seaborn and Matplotlib are two of Python's most powerful visualization libraries. Seaborn uses fewer syntax and has stunning default themes and Matplotlib is more easily customizable through accessing the classes.
  • Which Face is Real? - 02 Apr 2019
    Which Face Is Real? was developed based on Generative Adversarial Networks as a web application in which users can select which image they believe is a true person and which was synthetically generated. The person in the synthetically generated photo does not exist.
  • Gold BlogR vs Python for Data Visualization - 25 Mar 2019
    This article demonstrates creating similar plots in R and Python using two of the most prominent data visualization packages on the market, namely ggplot2 and Seaborn.
  • Silver BlogRunning R and Python in Jupyter - 19 Feb 2019
    The Jupyter Project began in 2014 for interactive and scientific computing. Fast forward 5 years and now Jupyter is one of the most widely adopted Data Science IDE's on the market and gives the user access to Python and R
  • Logistic Regression: A Concise Technical Overview - 23 Jan 2019
    Logistic Regression is a Regression technique that is used when we have a categorical outcome (2 or more categories). Logistic Regression is one of the most easily interpretable classification techniques in a Data Scientist’s portfolio.

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