On Reading Data Science Blogs 1: Principles

There are lots of reasons why you read a data science blog, such as procrastinating doing something more important. But you probably relates to this post the most if you read blogs to explore techniques and ideas and on your eternal quest of being a better data scientist.

This post particularly introduces the two important principles I recall regarding to reading. In the later posts I will cover other aspects of reading data science blogs such as techniques and examples. All of my posts are my subjective opinions so feel free to disagree. I hope you could eventually find something valuable.

In general, I recommend you to keep these in mind:
1.Many blogs are bad, but in different ways.
You could judge a blog by its value/content, writing, representation or whatever metric you can think of. I find often time valuable information is not presented in the format easy for me to digest. For instance, William Briggs’s blog posts offer me many good insights on statistics but also are written in a dry, philosophical language. Also I used to read a book that has good content but does not have page numbers. Thus it is very difficult to find particular chapter.

2.Read to gain value, although it may often take you lots of time, effort or both.
One metric you could use to measure the success of your reading, or the article you read, is the short term or long term differences between reading and not reading. For instance, you could read a blog and copies the codes to save you a few hours on your hw/project. Or a blog could give you some good advice and principles, if implemented properly, could benefit your job, or whatever aspects of your life in the future. “In the future” means you could see the obvious results in several days, or several months, or probably several years and decades (Think about the benefits of you reading and memorizing the multiplication table.)
To gain value, you have to do more than reading from start to end. Reading without proper follow up is like reading a textbook or going to a lecture for a class without doing any homework. The difference is, studying in a class, you will have exams to challenge your understandings while reading a blog, nobody will check if you actually gain anything from it or not.

In the next post (coming in a week), I will go over how I read Advice For New and Junior Data Scientists.

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