Optimize Your Data Science Environment

Ido Shamun on May 23, 2019

I have entered the world of data science in the last couple of years, coming from the engineering and devops side. I think the perspective of an en... [Read Full]
markdown guide

Great post, sounds like your background is going to make things easier when it comes to infrastructure and deployment.

Are you facing any challenges in your move to Data Science?


Thanks for the kind words :)
There were some challenges indeed in this transition. First of all data science requires a lot of knowledge and background that I partially possessed so I had to learn it through online courses and great colleagues. Second, you have to get used to the fact that everything takes time. As an engineer you are used to immediate feedback, you change your code and instantly can enjoy the results. Here it's totally different it can hours or even days to do one iteration so you must develop patience (for me it was one of the hardest things to do).
Lastly, you need sometimes to shutdown the engineering part in your head and just do what you want, without thinking about performance, memory consumption, etc. Just do it and then fix whatever needs to be fixed.
Probably there were some more challenges but these are totally the major ones

code of conduct - report abuse