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Found 4 results

  1. Hello everyone, I received offers from the following master's courses in the UK and would be really interested in some comments about what might be the best route to take in my situation. Specifically, what I'm interested in are topics in macro modelling and computational economics, econometrics (especially time series) and machine learning and its applications to econometrics. My offers are for these courses: Oxford MPhil Economics LSE MSc Econometrics and Mathematical Economics (EME) UCL MSc Machine Learning Cambridge MPhil Economic Research I know there are already tons of posts comparing the relative merits of the LSE EME and Oxford, Cambridge etc. but what I don't really know is whether I might not be better off doing an MSc in Machine Learning rather than the more traditional economics courses since I think they have very little, if any, coverage on the computational and ML side. The EME might be the exception since I could do modules in the stats department on modern computational methods. Also, does anyone know of potential PhD programmes that have strengths in these areas? Would I lower my chances of getting into a top US PhD programme doing an MSc in Machine Learning rather than the EME? Or could that be a strength because it would give me the preparation to use these tools in my research? At the moment I am still undecided between LSE, UCL and Oxford. (I think the Oxford programme dominates Cambridge for me - am I wrong?) Funding is another issue - and should I get a scholarship for any of the three programmes I am likely going to do that. Thanks very much for your help!
  2. Just want to check what you guys think about the application of data mining/machine learning/deep learning and other AI techniques in economics field. I heard that some researchers have been doing this, but haven't looked at their work yet. Also wonder if any PhD programs pay specific attention to this track? Thanks!
  3. I have not been very active on this forum since I started my masters program and taking 21.5 credits (sleep is not THAT important), but I have come across an interesting conundrum. I am working as an RA for a professor and have become interested in the application of machine learning to finance problems such as pinning down high frequency traders on TAQ data to isolate the effects of HFT and determine if HFT is making markets more or less efficient. My main question has now come down to this: Is it going to be a potential negative to focus a research paper on this type subject when applying for a PhD in Finance as compared to sticking with a more traditional research topic? Thanks for your help!
  4. Hello All, I'm a 3rd year (domestic) computational physics major with a strong interest in machine learning (stemming from my physics research). I would like to transition from "physics" to computer science for my graduate studies. Currently, I've taken the following CS courses: Intro to Comp Sci Data Structures Discrete Math Algorithms Network Programming Several good ML schools (UTA UWash etc) encourage students from non CS disciplines to apply but highly recommend certain courses as background (computer organization, operating systems, and other 'standard' cs courses). My research in ML is purely through a few years of research with different physics applications (particle physics/ astrophysics), and my formal background in this area has been through self-digested textbooks and video tutorials. So here's the bind: This upcoming semester will be the last semester of CS coursework that is guaranteed to be on my transcript for CS grad apps. I'm currently enrolled for the following courses: Optimization Techniques Mathematical Statistics Advanced Electricity and Magnetism (Physics course, irrelevant here) Computer Organization There's no explicit ML courses offered this upcoming semester however there is a course in web mining that is offered at the same time as comp org. Would I be better off taking the course in web mining and pushing off comp org and os to my senior year? Web mining would give me another course in the field I want to pursue in grad school but comp org might fill some basic requirements (of course I could explain that I'm taking these courses in my personal letter, or something...) Any advice would be much appreciated. PS) IF it matters, assume my research background is strong, my GPA is perfect, and I will have some good recs. PPS) Perhaps if I left out some of the standard coursework (focusing more on ML-related topics) but scored > 90% on the GRECS?
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