This post provides a simple example demonstrating how a shell script can be called with appropriate variables from any Org file in Emacs. The script essentially converts a Jupyter notebook to Org source, and Babel is leveraged to call the script with appropriate variables from any Org file. This reddit thread and blog post elucidate the advantages of using Babel and Org mode over Jupyter notebooks. Directly editing code in a Jupyter notebook in a browser is not an attractive long term option and is inconvenient even in the short term.

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I like to have any reading material and my notes side by side1. This is easily done with Emacs by splitting the buffer vertically (C-x 3)2 For example: Once a link has been opened via w3m, I hit org-capture (C-c) with a preset template that grabs the URL to the article along with the created date in the properties, with the cursor in position ready to take notes. (setq org-capture-templates '(("l" "Link + notes" entry (file+headline "~/my_org/link_database.

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Title: Navigating Diverse Data Science Learning: Critical Reflections Towards Future Practice Author: Yehia Elkhatib Download link This are my notes on the above paper, which mainly deals with detailing the methods explored and implemented to impart a high quality of education in data science. The paper also provides an interesting breakup of the different roles in data science workflows. The importance of being able to work in a team is highlighted.

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I’m an admirer of Howard Abrams, especially because his posts and videos show the awesome power of doing things in Emacs, and the importance of writing clean and logical code. Watching his videos and reading his posts make me feel like I was born yesterday and I am just getting started. But more importantly, they also fire up my imagination regarding the possibilities out there and the potential to create glorious workflows.

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It’s a well known trick that installing a SSD in place of the conventional Hard disk can breathe new life into very old machines. My mid 2010 Macbook Pro is one such example, being over 8 years old. In particular, within Emacs - mu4e responds much more quickly and there is significantly less lag in searching / accessing emails and HTML rendering. The other advantage of using a Mac over Linux is that installation and setup instructions are more often available out the box for the Mac OS (though this is changing).

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Projects

CFD Post Processing automation

python script to help automate post processing of simulations, by applying an extraction macro on multiple result files.

Contributions to the CFD-Online Wiki

Documentation (based on actual exploration) to the popular CFD-Online wiki related to getting started with Open Source CFD.

Simulation job scheduler

python script to manage and schedule ANSYS CFX simulations on designated computing clusters.

Current Trends of Emission Reduction Technology in Vehicular Diesel Engines.

This project undertakes a technology study and survey covering the methods to controlling harmful emission from Diesel engines in particular and the efficacy different technologies. It explores current emission norms and the contradicting formation conditions of NOx and CO

On-line Certificate Course: EdX HarvardX PH125.1x: Data Science: R Basics

The course covered an introduction to using R to extract, manipulate and thus analyse data. It basically lays the foundations to using R in data science.

On-line Courses @ Datacamp

Data Science related courses completed on Datacamp.

On-line Courses @ Dataquest

Course competition certificates from Dataquest.

On-line Courses: Code School

Several courses covering python, git, SQL,regular expressions

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