I’ve been thinking1 about having a blog for a long time and it’s not the first time. As an example, in the About me section of the blog I have listed the links to some of the previous blogs that I’ve created in the past, the ones I’ve been playing with for some time, without giving too much continuity to the majority of them.

Enough!!

I said to myself.

I know of the potential benefits of having a blog, among other reasons as a support or aid to the self-study process. Reflecting on this I’ve come across a tweet with the link to a post on Medium by Rachel Thomas 2 in which she clearly explained the reasons why everyone should have a blog.

Having a blog and giving continuity to it gives rise to moments of reflection and facilitates putting ideas into writing, as well as having a space to come back again to recover what you left written down at some point before, something that you may need to review.

It took me a while to decide what to use and in the end I opted for Hugo (in the past I tried Jekyll and Pelican, especially the first one), although currently the ecosystem of static site generators is huge. I’ve recently tried other options like Gatsby, Hexo and blogdown, but for various reasons, mainly blog generation speed and simplicity, I have finally opted for Hugo. For the deployment of the generated code I had in mind to use Github Pages again, as in my previous blog, but I guess I’ll finally try Netlify and I think it will be a better option.

I am not sure if I will make the blog fully bilingual or only for certain entradas (sorry, posts), which may be only in Spanish or English. We will see. I do want to have a place to rest my notes on the books I read. In fact, I already have a few pending to include. This is also a topic that motivates me to have the blog. Reading technical topics is fine, but if you don’t take a look at what you’ve read, it’s also easy to forget.

Footnotes

  1. Originally published in July 2021, when TheDataIsFlat.com was a regular blog site.

  2. Rachel Thomas is co-founder of fast.ai, a place of reference for Deep Learning, as well as a professor at the USF Data Institute.