Super DataScience podcast

I am working my way through the Udemy data science course “Machine Learning A-Z” by Kirill Eremenko and Hadelin de Ponteves. The course steps through key machine learning algorithms and approaches using Python and R. As an R programmer, it’s great to compare to the Python code and learn it’s syntax. From my nascent observations, it takes fewer lines to code an approach with R compared to Python.

Kirill and Hadelin are clear communicators. They break-down complex information, guiding the viewer with palatable bite-sized chucks of information. I was so impressed that I sent Kirill a thank you on Udemy. Kirill responded, we added each other on LinkedIn, then he invited me as a guest on his podcast at Super DataScience!

My episode can be found here, here and here. Three links, same episode - Woo!

Thanks to Kirill for having me as a guest and giving me an excuse to talk about neuroscience – something I haven’t done for the past three years. The dorsal lateral prefrontal cortex got a mention :)

Probably a better way – Year one

It’s been a year since my first post, and a lot has changed. Looking over my early posts, I’m amused that I started with VBA in Excel. At the time I had completed a VBA training course and was writing a program at work. I saw a future of working exclusively in VBA – writing VB scripts where my customers would use my awfully clunky workbooks to manage and analyse their data. I suspect if I searched “VBA” across job ads, the number of hits has reduced since a year ago.

Soon I commenced the Data Science courses on Coursera. I learnt to program in R via these courses (aided with prior Matlab knowledge) then applied this knowledge at work. I managed my data with R and visualised data with R. I even built a web app (using the Shiny package). R is great, and it’s free. Not like how Facebook is free where one hands over personal data. R is proper free.

I am regularly using R in my new role. I do wonder whether I should learn Python. My understanding is that Python excels over R in web applications and text analytics. I wish I knew Javascript – I would like to create custom interactive displays.

I’d love to know more about statistics and multiple regression. Not entirely sure how I would apply this knowledge. At the heart of it, I’d like to be in a position to receive a large amount of data and simply know what statistical methodology I should be applying towards uncovering insights. I have commenced reading my thick stats book mentioned in this post.

At the moment I am being exposed to different data types and methodologies at work. JSON, XML, MySQL. I’ll take them as they come. I’m fortunate that I am surrounded by developers that have advice when I get stumped. I just have to be more comfortable with asking for help.

Summary: Year one was moving away from VBA to R. Here’s to year two!