What happens out there? In the Real-World, With R

This talk contains two sections predominantly - 1st explaining what’s all (non-obvious) that are possible with R and 2nd, How well-known organizations are using R in their company. R is one of the most popular programming languages preferred in Data Science / Analytics.

 
 

Outline/Structure of the Talk

https://github.com/amrrs/RinTheRealWorld

Learning Outcome

Knowing the power of R, better!

Target Audience

Those who are already in Data science

schedule Submitted 7 months ago

Public Feedback

comment Suggest improvements to the Speaker
  • Usha Rengaraju
    By Usha Rengaraju  ~  7 months ago
    reply Reply

    Hi Abdul ,

    Thank you for the proposal submission. Could be please mention the learning outcomes for this talk and not point it to github link. 

    Thanks and Regards,

    Usha Rengaraju

     

  • Dr. Vikas Agrawal
    By Dr. Vikas Agrawal  ~  7 months ago
    reply Reply

    Dear Abdul: I am trying to understand what R-specific problem solutions do you plan to show. Also, I am trying to see what specific advantages of R exist for enterprise deployments. Do you plan to cover these? Warm Regards, Vikas

    • AbdulMajedRaja
      By AbdulMajedRaja  ~  7 months ago
      reply Reply
      Hello Dr. Vikas, Did that help you?
    • AbdulMajedRaja
      By AbdulMajedRaja  ~  7 months ago
      reply Reply

      Hello Dr. Vikas, Current plan is to cover the stuff in the deck where in the 2nd part it covers about a few companies like Uber / SO/ Airbnb on how they're using R internally. But if that's of something your interest and if you think would help audience. I can add that too - There's a case of T-mobile doing that - using R in Production (along with Deep learning models). 

      Abdul


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    Parul pandey - Jupyter Ascending : The journey from Jupyter Notebook to Jupyter Lab

    Parul pandey
    Parul pandey
    Data Science Communicator
    -
    schedule 8 months ago
    Sold Out!
    45 Mins
    Demonstration
    Beginner

    For many of the researchers and data scientists, Jupyter Notebooks are the de-facto platform when it comes to quick prototyping and exploratory analysis. Right from Paul Romer- the Ex-World bank chief Economist and also the co-winner 2018 Nobel prize in Economics to Netflix, Jupyter Notebooks are used almost everywhere. The browser-based computing environment, coupled with a reproducible document format has made them the choice of tool for millions of data scientists and researchers around the globe. But have we fully exploited the benefits of Jupyter Notebooks and do we know all about the best practises of using it? if not, then this talk is just for you.

    Through this talk/demo, I'll like to discuss three main points:

    1. Best Practises for Jupyter Notebooks since a lot of Jupyter functionalities sometimes lies under the hood and is not adequately explored. We will try and explore Jupyter Notebooks’ features which can enhance our productivity while working with them.
    2. In this part, we get acquainted with Jupyter Lab, the next-generation UI developed by the Project Jupyter team, and its emerging ecosystem of extensions. JupyterLab differs from Jupyter Notebook in the fact that it provides a set of core building blocks for interactive computing (e.g. notebook, terminal, file browser, console) and well-designed interfaces for them that allow users to combine them in novel ways. The new interface enables users to do new things in their interactive computing environment, like tiled layouts for their activities, dragging cells between notebooks, and executing markdown code blocks in a console and many more cool things.
    3. Every tool/features come with their set of pros and cons and so does Jupyter Notebooks/Lab and it is equally important to discuss the pain areas along with the good ones.