Asking The Right Question

Buck Woody argues that the hardest thing about data science is asking the right question:

When I started down the path of learning Data Science, I was nervous. I have to work hard at math – it’s a skill I love but one that does not come naturally to me. I was nervous because I thought the most daunting task I would face in Data Science waslearning all the algebra, statistics, and other maths I would need to do the job.

But I was wrong.

Math isn’t the hardest thing in Data Science. Actually, since it’s so mature, and documented, and well-known, it’s quite possibly the easiest thing to conquer in the skillset. No, the hardest thing about Data Science is asking the right question.

I’ll lodge a bit of a disagreement here.  I’m okay with the argument that asking the right question is the toughest part, but the math’s not particularly easy either…  Knowing when to use which distribution, which model, and which parameters requires a definite amount of skill.

Related Posts

Calculating AUC in R

Andrew Treadway shows how you can calculate Area Under the Curve in R: AUC is an important metric in machine learning for classification. It is often used as a measure of a model’s performance. In effect, AUC is a measure between 0 and 1 of a model’s performance that rank-orders predictions from a model. For […]

Read More

Python versus R (Again)

Alex Woodie looks at whether Python is dominating R in the data science space: There is some evidence that Python’s popularity is hurting R usage. According to the TIOBE Index, Python is currently the third most popular language in the world, behind perennial heavyweights Java and C. From August 2018 to August 2019, Python usage surged […]

Read More

Categories

January 2016
MTWTFSS
« Dec Feb »
 123
45678910
11121314151617
18192021222324
25262728293031