Topics: AI | Data Science | Data Visualization | Deep Learning | Machine Learning | NLP | Python | R | Statistics

About Asel Mendis

Asel Mendis is a GIS Analyst, Data Science Editor and Writer who continues to learn and uses Statistics, Machine Learning and technology to create insights and value. He is a Contributing Editor at KDnuggets, the largest Data Science knowledge sharing platform in the world. He has interests in Machine Learning, Data Visualization and Statistics using R and Python. He has a Master of Analytics from the Royal Melbourne Institute of Technology in Melbourne specializing in Applied Statistics. Follow him on Twitter (@aselmendis) or connect with him on LinkedIn.

Asel Mendis Posts (27)

  • Silver BlogJupyter Notebooks: Data Science Reporting - 06 Jun 2019
    Jupyter does bring us some benefits of being able to organize code but many of us still find ourselves with messy and unnecessary code chunks. Here are some ways including a NEW EXTENSION that anyone can use to begin organizing your code on your notebooks.
  • 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.
  • Silver BlogGold 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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