How is text created and rendered to the screen? Computer Science |
- How is text created and rendered to the screen?
- Quantum Chemistry Breakthrough: DeepMind Uses Neural Networks to Tackle Schrödinger Equation
- What are your "no one can use my computer unless i tell them what key on the keyboard does what"?
- Ready to receive all of the criticism lol - art history undergrad wanting to pivot toward CS
- Task Scheduler Problem [Asked by ����Facebook]
- Applications of Artificial Intelligence (AI) in the Food Industry
- Resources for learning Hoare Logic/Getting better at proofs
- Become job ready in less than 12 months with Coursera Professional Certificates
- Understanding Stochastic Gradient Descent intuitively...
- Getting into top CS PhD program
- Distributed computing project to check convergence of the Collatz problem
- New AI Technique Builds Dynamic Images From a Single Photo
- What are some exciting side project ideas for a final year CS grad?
| How is text created and rendered to the screen? Posted: 18 Sep 2019 11:45 PM PDT I understand how shapes can be made from a bunch of vertices but is that really the same way text is created? Wouldn't it require a lot of vertices to create all those tiny characters on the screen? I'm just trying to understand how graphics are created at the lower level so if you could point me in the direction of any other good resources that would be great. [link] [comments]  |
| Quantum Chemistry Breakthrough: DeepMind Uses Neural Networks to Tackle Schrödinger Equation Posted: 18 Sep 2019 11:58 AM PDT |
| What are your "no one can use my computer unless i tell them what key on the keyboard does what"? Posted: 19 Sep 2019 03:26 AM PDT My personal are:
inspired by: [link] [comments]  |
| Ready to receive all of the criticism lol - art history undergrad wanting to pivot toward CS Posted: 19 Sep 2019 01:47 AM PDT Hello all! Background: I have about 6 years of experience in museums and am finishing up my undergrad in Art History. I started undergrad absolutely set on doing a PhD and working in museums. Got really ill about 1/2 way through undergrad, took a bunch of time off, and didn't have the time or forethought to take any CS prerequisites. I'm now just trying to finish up my undergrad and have absolutely zero interest pursuing art history further than I have. It's great, but it's just not what I want to pursue and, honestly, the pay is just not realistic. I've been reflecting and my favorite aspects of my museum jobs have been working with and learning to build databases. I'm really heavily considering pursuing a masters in CS or Informatics so I can potentially work with museums as a consultant to help manage their databases as they move further toward digitization (it's becoming more common for museums to outsource these projects instead of hire new staff) or have the opportunity to do database design/management in a different industry. Some of the bigger institutions (MoMA, Met, Art Institute) hire software developers/database administrators. Currently, I plan on taking a look at my university's different CS or Informatics tracks and taking a few basic classes next semester to fill my three open elective spaces. If this sticks, I'd pursue further education through a certificate program or community college classes before looking into an online masters for non majors - possibly Georgia Tech, Penn, or any other relevant program that I can get into. I don't want to get a second bachelors and genuinely don't see it as a necessary step. Have any of you made the transition later in undergrad and what did your career path look like? Any recommendations/advice? GRE? Please ream me, I know this is such an annoying post. [link] [comments]  |
| Task Scheduler Problem [Asked by ����Facebook] Posted: 19 Sep 2019 12:32 AM PDT |
| Applications of Artificial Intelligence (AI) in the Food Industry Posted: 18 Sep 2019 11:25 PM PDT |
| Resources for learning Hoare Logic/Getting better at proofs Posted: 18 Sep 2019 12:43 PM PDT Heya! I'm currently a student hitting my upper level Data and Structures course at Uni, but decided to take it at the Honors level. The prof is awesome, but has a flair for proofs. While I am familiar with Induction, Contradiction etc. He is requesting proofs of the efficiency of our algorithms for each project we submit. I've managed to do this slowly for projects that I have due, but am worried I won't be able to keep up if I have to do it on an exam. Our textbook does not seem to cover this logic and the notes that he provided only have one example that is difficult to extrapolate in all cases (Especially because it doesn't specify how to deal iwth proofs that will have more edge cases). Does anyone have resources explaining algorithmic proofs for idiots? I'm at the undergrad level here, and would really appreciate a hand-holdey approach that gives me examples that I can check my own work against. So far I have only found relatively dry papers, and while I am working through those they seem to be targeted at the grad level or above. Thanks! The book we are using is "Data Structures and Algorithms Analysis in Java (Weiss)". I have referenced "Algorithms" from Princeton on my own time. The book is...kind of awful for explaining any concepts for actually doing the proofs, so I'm looking to expand my horizons here. [link] [comments]  |
| Become job ready in less than 12 months with Coursera Professional Certificates Posted: 18 Sep 2019 11:44 PM PDT |
| Understanding Stochastic Gradient Descent intuitively... Posted: 18 Sep 2019 12:51 PM PDT |
| Getting into top CS PhD program Posted: 18 Sep 2019 09:27 AM PDT I am a third year Physics undergrad at top UK university, with reasonably good grades (close to the top of the year). Recently (about 6 months ago) I became really interested in machine learning and have been reading a lot/doing online courses/getting experience on Kaggle. Not an expert so far obviously, but seriously considering moving into the field in the future because it is exciting for me, and also because of employment opportunities. So far I have done two academic internships (in top institutions in UK and US), both in different areas of computational physics but not in ML explicitly. Since I am quite far from being an expert in the field right now, I am considering to become one by doing a PhD in machine learning (and go into industrial RnD/data science after). However most PhD students in my university's CS department did CS undergrad. I am wondering what are my chances, given that I constantly improve my ML skills, have an extensive experience in computational physics and excellent academic record, to get into the CS PhD in ML (not necessarily at my uni but at another top uni). Thanks! [link] [comments]  |
| Distributed computing project to check convergence of the Collatz problem Posted: 18 Sep 2019 07:33 AM PDT |
| New AI Technique Builds Dynamic Images From a Single Photo Posted: 18 Sep 2019 08:10 AM PDT |
| What are some exciting side project ideas for a final year CS grad? Posted: 18 Sep 2019 11:32 AM PDT |
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