I have a basic question, mainly about the similarities and differences between data science (DS) and machine learning (ML). When I put it up on Stack Overflow, someone want to delete my post because he/she pointed out that my question is a question unrelated to programming. Fine. And then I went to this site and I put forward the question, but some people voted it down again.
After that I entered the Computer Science Stack Exchange site, but I found there was not a label for data science on that at all. What's more, when I was about to ask that, I had to wait for 40 minutes since I had asked a question on one of your subsites even though I had deleted it. So I am wondering where can I post it so as to get kind answers?
On top of that, I have a suggestion: Could you Stack Exchange provide suggested sites to those who posted inappropriate questions or move the posts to correct sites automatically so that they do not have to find one from the overall 175 sites and wait for an additional 40 minutes intervals?
This is definitely an inefficient process and a pure waste of time, for me, and for those patient teachers.
Edit: @PolyGeo reminded me that I should ask only one question rather than three in each post. It really makes sense, but the point is, can't this problem be solved by just one edit instead of deleting it and finding somewhere else and waiting for a long time? Besides, different people hold different opinions or doubts on my question. Some may say my question is excursive. What can I do?
Following @PolyGeo's advice, I modified my original question as follows (I am not going to ask here; please do not say I am out of topic). And my question again, where can I post?
Recently I took part in an online project about data science, I learned some frameworks such as Pandas, NumPy, and Sklearn, some basic knowledge, like kNN, linear regression, regularization, logistic regression and classification/regression trees. Although I have finished the course, I am still having a hard time writing my resume for an application of MS, describing the relationship between what I have learned with artificial intelligence (AI), or machine learning. Since I am going to pursue the field of AI, how can I figure out the similarities between DS and ML/AI so as to express my previous work?
A couple of days ago, I glanced over Coursera and found the machine learning course provided by professor Andrew Ng is extremely similar to my previous course except neural networks. My course did not cover that.
In a nutshell, my question is, what are the links between what I have learned with machine learning or artificial intelligence?
