Disclaimer: I’m still in the process of figuring out the best learning pathway. Rest assured, I will be documenting them

Author : gkarem
Publish Date : 2021-01-07 09:13:01


Disclaimer: I’m still in the process of figuring out the best learning pathway. Rest assured, I will be documenting them

If there’s one thing that frustrates me about the data science process, it would probably be the fact that I could spend hours (and maybe days) building and refining a model only to realize putting it in production is another ton worth of work and requires getting the help of more specialized people.

Whenever I try to think of ideas on how to approach a problem with data science, I always get stalled by the brain-racking step of translating it into a form that can be consumed by other people (my stakeholders).

I want to have a better perspective of what goes in the mind of developers I work with. I want to learn best practices in programming that extends beyond my Jupyter notebook.

An open-source Python library for working with n-dimensional arrays and offering an extensive set of tools for numerical operations to achieve enhanced performance and faster execution times.

Moreover, I realized while I’m comfortable with coding in Python/R and getting my data using SQL, my scripts often look dry and often require a lot of refactoring afterward. I get things done with my code but sometimes my notebooks are not in a state I’m proud to share with other people.

Furthermore, I realize how boring typical portfolio websites could be — as more often than not, you just present your analysis and results in a very static way. However, some do take it to the next level. JP Hwang, in his article, compiled a few data science portfolios that will definitely awe and inspire you.

While there’s nothing wrong about using a blogging site for a portfolio, it took me painstakingly three more long years to realize how a self-hosted site (or even just a simple GitHub page) will do and 100x better (and cheaper!) than a blog site on a premium plan.

I know I need to become more technically proficient, in a holistic manner. I want to become knowledgeable to a point I can engage with my more technical counterparts at an almost equal level.

I’m one of those data enthusiasts who had a bit more math in university than your average programmer and who happen to decide I want to use code to do some data magic to make some business people happy.

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hes that recommender systems would get better at surfacing niche content, rather than fueling rich-get-richer effects. Yet, in response to those who point out that we’re living in a world that is more hit-driven than ever, Anderson says people may have gotten excited by the idea that the Long Tail era was the end of the blockbuster — but he never actually said that. He says, “It was the end of the monopoly of the blockbuster.”

An open-source Python library for working with n-dimensional arrays and offering an extensive set of tools for numerical operations to achieve enhanced performance and faster execution times.

Luckily, I get to make use of a lot of my scientific acumen and problem-solving in approaching business challenges with data. Two years in as a data scientist, I realized I’m not as well versed as I thought I am with software and other tech stacks that can make my life as a data professional much easier and effective.

Don’t get me wrong. I’m not saying that you should become a web developer yourself. I’m not saying you can’t build a good portfolio website without going in-depth in web development.

I’m trained in the natural sciences. To be specific, I did my undergrad in Chemistry and finished a master’s in Bioprocess Engineering. I had fun researching on natural products and designing composite biomaterials.

I envy people who know how to deploy apps that demonstrate the value of their project. Hence, I want to learn more about web development to learn visual and interactive ways to share my work.



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