Become Language Agnostic by Combining the Power of R with Python using Reticulate



Language Wars have always been there for ages and it's got a new candidate with Data science booming - R vs Python. While the fans are fighting R vs Python, the creators (Hadley Wickham (Chief DS @ RStudio) and Wes McKinney (Creator of Pandas Project)) are working together as Ursa Labs team to create open source data science tools. A similar effort by RStudio has given birth to Reticulate (R Interface to Python) that helps programmers combine R and Python in the same code, session and project and create a new kind of super hero.


      * Why R and Python?
           * Moving away from R vs Python
           * Cases where both the langauges together will help
      * Introduction to Reticulate
           * What's about the package `reticulate`
           * How to install reticulate
           * Basic Functions
        * Python Engine
           * Understanding about Python Engine in the local Machine
           * Select Different Engine for Reticulate Session
        * Code Outline
           * Layout/Structure of the Code
           * Presence of R
           * Presence of Python
           * Object Interaction
        * Sample Use-case Explanation
           * What's the use-case
           * Spacy - Outline
           * RMarkdown - Outline
           * Combining Spacy and Rmarkdown with Reticuate
           * NLP Analysis Report
        * Potential use-cases to create a new super power
           * Use-cases that audience can take back


Knowledge of R and Python

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Speaker Info:

Abdul Majed is an Analytics Consultant helping Organizations make sense some out of the massive - often not knowing what to do - data. Married to R (but dating Python). Always amazed by Open Source and its contributors and trying to be one of them.

Organizer @ Bengaluru R user Group (BRUG) Organizer

Contributed to Open source by publishing packages on CRAN and PyPi

Writer @ Towards Data Science and DataScience+

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Id: 1067
Section: Data Science, Machine Learning and AI
Type: Talks
Target Audience: Intermediate
Last Updated: