PlanetTerp VS Installation

I’ll preface this by saying that my initial/primary major is in the College of Behavioral and Social Science (BSOS). I added my business major as a secondary major in my sophomore year, so I’m probably not the best to describe the initial freshmen adjustment period, but rather comparisons with the other department. Regardless, I think overall, I’ve had an enjoyable experience with professors and classes within the business school. Most professors will post their PowerPoint slides and stick to the syllabus schedule to the best of their ability. Sometimes, they record their lectures in case students cannot attend due to sickness, interviews, or other circumstances, but I’ll warn that not every professor does that. All the professors I have had were very responsive to emails and open/friendly during office hours. They are all passionate about their careers and subject areas and willing to guide students; I have received referrals to companies from professors. As a general resource for any UMD class, you can use the website PlanetTerp (https://planetterp.com) to look up classes, professor reviews, and grade distributions.

Getting an A or B in MATH120 is definitely reasonable. Especially if you choose some of the good teachers (use planetterp.com to see reviews but I recommend Archana Khurana)

According to planetterp.com, you'd have about a 30% chance of increasing your grade assuming that you're an average student and that your grade is determined entirely by chance. Another thing to consider is whether having one less class in your semester's coursework would increase your GPA enough to make it worth taking when you could be focusing that energy toward studying for your other classes (which you will need) or toward something fun.

In terms of quality of professors I think the ones I have had so far are good, but if you want to do look at like overall you can search up teachers and classes for ratings and grades: https://planetterp.com/

Hey all hope everyone enjoyed their break! In case you haven't heard, PlanetTerp is now open source so anybody can contribute! We want the UMD community to be involved with the development of the site and have a say in the future of it as well. Whether you found something not working correctly, have an idea for a new feature, or something else, we wanna hear it. Take a peak at our Github to see what features we have in the works or what issues you might be able to help out with! If you have any questions or want to be apart of the discussion feel free to join our discord!

You can go to planetterp.com to see exact grade data and percentiles even stratified by professor. That way if you know about how well you are doing relative to everyone else you can kind of guess your grade

Here you can look at average grades received by students in courses as well as rating of the faculty who teach them

"The site" is actually just their blog. The github repo at https://github.com/netbox-community/netbox is more like the real homepage and has a good presentation.

Sweet! If it ends up anything like Netbox it will be so sweet. By looking at the screenshots I am very excited to see this implemented!

NetBox Release v3.6.6 is now live (as of November 29, 2023)!

Take a look at netbox. https://netbox.dev/

Pre-trained systems dominate AI today (as deep as the P in GPT). My team and I have been researching and building alternatives given how the hallucination, blackbox and other problems don't seem solvable within* the current paradigm.

One of our first applications is a network automation solution for Netbox-- locally trained AI Agents unique to each Netbox account to predict roles of newly added devices given the current local list of devices, like a context-aware autocomplete.

Agents are lightweight by design, this particular Netbox Agent is 40-neuron, and when hooked up demo.netbox.dev and consistently gets 80%+ accuracy predicting device roles even when trained on ~60 devices only.

Try it out: https://aolabs-netbox.streamlit.app/

You can use dummy data from demo.netbox.dev. More on Netbox: https://github.com/netbox-community/netbox

We'd keen for feedback, if this is useful, how we could extend it if it is, or if it sparks other application ideas.

* Somebody has to be the pre-trainer, leaving an irreducible gap of misunderstanding between AI and its application which we are trying to diminish by adding a layer of local training.

Before upgrading, please: 1. Verify in release notes changelog if any new breaking changes might affect you. You can also review the NetBox Issues on GitHub to see if any new issues have arisen that might affect you. 2. Next, refer to the Upgrading to a new NetBox Release guide for steps to upgrade your instance.

I've been looking into some projects for some opensource software i use and noticed a few of them have empty __init__.py files (for example https://github.com/netbox-community/netbox/blob/develop/netbox/core/__init__.py)

IT wise, It's been a fair few years since I've been in a department that does asset management, we used to use GLPI with it's warts and all, which got replace with https://github.com/netbox-community/netbox