MS in Stats to PhD ML via MSCS

[kingduck]

I typically lurk on the mathematics and statistics section of this website. I've been noticing recently that ML seems to be more housed in CS departments, while still drawing upon knowledge in stats, e.g. CMU's ML PhD has a couple courses on statistics as part of their curriculum. 

The last two years, I worked in analytics while I earned an MS in Stats from a large state flagship, ranked USN top 50 in the field. I am contemplating on earning an online MSCS from UT Austin or GATech since I have always had an interest in programming and studying efficient algorithms. I have also taken a few into to CS courses, and I have had to code extensively at my job. Given my stats background, I am also interested in ML and the overlap between stats and CS. A couple programs that I've seen offer ML are GATech PhD in ML, CMU PhD ML, and Stats+ML in the UK (i forgot with universities were involved in this group). 

I finished undergrad with a 3.3 in economics (low econ and gen ed grades, high STEM grades) at a top 20 USNR private school, and I finished my masters with a perfect GPA.

As the computer science field is very much new to me, is there any advice for me on performing doctorate level research ML? Would I have a chance at applying into CS departments that have a focus in ML? What is the consensus on the OMSCS approach?

[limnakhau]

I applied to PhD programs this past cycle and was rejected by all. I plan on trying again in a future cycle but was wondering how I can gain experience related to ML/NLP especially given that I have already graduated. My GPA was a ~3.3 and while I do have some research experience (mainly a data science REU in my senior year) I didn't get much exposure to anything ML related until taking a graduate level NLP course in my last semester.

I did some side work with a professor and another project with a couple of postdocs but this was either short term or dropped off as my full time job began to take up more time. Right now I'm still looking to see how I can gain experience in this exciting field while I'm still working. Should I continue to ask professors in nearby universities even though I'm not actively enrolled as a student. Or could I also ask those in my current company (even though they aren't necessarily as involved research-wise)?

 

[limnakhau]

On 12/22/2020 at 3:46 AM, kingduck said:

I typically lurk on the mathematics and statistics section of this website. I've been noticing recently that ML seems to be more housed in CS departments, while still drawing upon knowledge in stats, e.g. CMU's ML PhD has a couple courses on statistics as part of their curriculum. 

The last two years, I worked in analytics while I earned an MS in Stats from a large state flagship, ranked USN top 50 in the field. I am contemplating on earning an online MSCS from UT Austin or GATech since I have always had an interest in programming and studying efficient algorithms. I have also taken a few into to CS courses, and I have had to code extensively at my job. Given my stats background, I am also interested in ML and the overlap between stats and CS. A couple programs that I've seen offer ML are GATech PhD in ML, CMU PhD ML, and Stats+ML in the UK (i forgot with universities were involved in this group). 

I finished undergrad with a 3.3 in economics (low econ and gen ed grades, high STEM grades) at a top 20 USNR private school, and I finished my masters with a perfect GPA. xvideos

As the computer science field is very much new to me, is there any advice for me on performing doctorate level research ML? Would I have a chance at applying into CS departments that have a focus in ML? What is the consensus on the OMSCS approach?

I got this,..