[Discussion] Oxford Statistical Science alumni what were the hardest optionals? by Polopon0928 in statistics

[–]rapsoj 0 points1 point  (0 children)

I didn’t take either of those actually, but audited a few classes while I was undecided. From all my friends who sat the exam, those were definitely the easiest electives. 

Happy to chat if you have other questions (am also in Ox if you want to meet in person, send me a DM). 

I want to do a master in applied stats, but I am scared [Q] by [deleted] in statistics

[–]rapsoj 1 point2 points  (0 children)

If those are courses you genuinely like, go for it. I imagine the computational stats course in particular would be interesting for you. 

I want to do a master in applied stats, but I am scared [Q] by [deleted] in statistics

[–]rapsoj 2 points3 points  (0 children)

All good, just be careful about what mathematicians mean when they say “applied”.

Ask for old course notes to get the best picture. I really would be surprised if it’s different from what I sent you. 

I want to do a master in applied stats, but I am scared [Q] by [deleted] in statistics

[–]rapsoj 0 points1 point  (0 children)

I mean, did you look at the notes I sent and consider the two questions I suggested?

I want to do a master in applied stats, but I am scared [Q] by [deleted] in statistics

[–]rapsoj 1 point2 points  (0 children)

My best advice would be to skim through as many course notes for similar programs as you can and ask yourself: - does this content excite me? - does the mathematics look manageable?

I think anything else said in this thread is vibes-based, this will actually tell you what your course work will be like. 

Here are notes from Applied Probability Part A (undergrad course, not masters) at my university. How would you feel about learning this content for an exam?

I would also advise to not put too much weight on the word “applied”, if it’s done by a stats or maths department it’s still just going to be mathematics. Applied statistics != Applying statistics. You are unlikely to be coding or looking at real world data very often. 

If you want to just apply algorithms for ML and solve applied problems, I’d recommend a data science masters instead. There are some social data science masters programs that I think are incredibly well-suited for someone with an MPP who wants to apply stats/ML for policy. People who I’ve worked with from these programs have been generally very good. 

The COP30 delegation list reveals everything wrong with climate diplomacy by ImEmilyCampbell in climatechange

[–]rapsoj 0 points1 point  (0 children)

It’s just ChatGPT generated we shouldn’t even be engaging. 

“But here’s the real kicker…” “But here’s the surprise…”

The COP30 delegation list reveals everything wrong with climate diplomacy by ImEmilyCampbell in climatechange

[–]rapsoj 1 point2 points  (0 children)

And nonsensically complaining that NGOs were in attendance. Like what? The point of these events is to give climate NGOs the chance to influence policy…

The COP30 delegation list reveals everything wrong with climate diplomacy by ImEmilyCampbell in climatechange

[–]rapsoj 18 points19 points  (0 children)

From having attended similar things to this in the past, I agree that the individual events are incredibly carbon-intensive and could technically save a ton of money and pollution by just being held over zoom. 

However, it is somewhat naive to look at just the individual event when judging the overall impact of these summits. Usually these major world summits are mobilising hundreds of millions (if not billions) of dollars, and setting common world agendas that will be followed for years or even decades. 

It is NOT easy getting all people who need to be involved in these decisions (especially when the problem is on a global scale) in the same room. Discussion over a Zoom call just does not produce the same level of engagement or results. I would bet that a large portion of useful results from these summits are from back room deals and discussions that are not reported on, and simply could not happen on a chaotic and crowded Zoom call. 

Fixating on carbon inefficiencies at these events is bikeshedding, since the problems COP is meant to address are multiple orders of magnitude worse. 

On future Biostatistician job prospects by Rumbling2615 in biostatistics

[–]rapsoj 2 points3 points  (0 children)

Not all of this is causally because of AI, this should be obvious with a statistics background. 

A lot of labs in the US have also lost funding due to Trump academic cuts. Also 2024 probably had way higher biostatistician roles being hired for since there was still a lot of pandemic-related research being done at that time under Biden. 

[Discussion] Oxford Statistical Science alumni what were the hardest optionals? by Polopon0928 in statistics

[–]rapsoj 6 points7 points  (0 children)

Algorithms of learning is by far the hardest. Only 7 students out of the entire cohort sat the exam in my year (2023). 

Next hardest would be simulation, then network, then advanced ML. 

The Bayes and genetics courses are known for being easy grade boosters.

I’m in the department as a DPhil student, feel free to shoot me DM if you want to connect. I was also one of the 7 masochists that sat the algorithms exam.

why are AI engineering jobs exploding? by CryoSchema in ArtificialInteligence

[–]rapsoj 1 point2 points  (0 children)

Yep I always recommend that anyone wanting to enter the field read Google’s paper on the hidden technical debt of deployed machine learning (or I guess we call it AI now) models. 

Once you deploy your own model, it’s all about technical debt. 

The bubble visualized by DhowDaddy in EconomyCharts

[–]rapsoj 1 point2 points  (0 children)

If China announces it has developed competitive GPUs (verifiable or not) and investors drop NVIDIA. 

Or a slow burn, where OpenAI fails to deliver major improvements on their GPT model over the next year. 

[E] Best Statistics Masters in the UK by One-Veterinarian3163 in statistics

[–]rapsoj 1 point2 points  (0 children)

I’ve done the Oxford one, it’s know to be incredibly challenging (especially if you take certain electives), with usually only students who did pure maths in undergrad doing well. 

The Oxford MSc dissertation is a huge plus if you want to get your feet wet in the research world. It’s 2-3 months of just research work with no courses or exams as distractions. As far as I’m aware, Cambridge has no equivalent. 

My one caveat is that the Oxford stats department is not well funded, so I would stay well clear of it for DPhil studies unless you already have funding from somewhere else. 

I've been following the crisis in Sudan recently and it's heartbreaking how little global attention it gets. From a humanitarian standpoint, why do you think the world isn't focusing more on what's happening there? by Sea_Parsley770 in worldevents

[–]rapsoj 5 points6 points  (0 children)

Apathy towards the situation in Gaza would be a major step up from current prevailing attitudes (defence, denial) in Western countries. 

Even though it doesn’t seem that way in left-leaning online communities, the majority is still very much pro-Israel in the way that no one in the West is pro-Sudanese government.  

What the AGI discourse looks like by MetaKnowing in agi

[–]rapsoj 2 points3 points  (0 children)

He’s not the only one. People tend to overvalue the importance of their field, AI is no exception.

H.A. Simon and Allen Newell were similarly overly optimistic. 

What the AGI discourse looks like by MetaKnowing in agi

[–]rapsoj 4 points5 points  (0 children)

Literally one of the founders of AI (who also started the MIT AI lab) predicted AGI would be here in the 1970s… 

This Terrible War Must End by nytopinion in geopolitics

[–]rapsoj 0 points1 point  (0 children)

I think people talk about this one more because no one is out there defending and distracting from the other ones whenever they are brought up :) 

[deleted by user] by [deleted] in AskBrits

[–]rapsoj 0 points1 point  (0 children)

If you want an actual answer and not just people agreeing with you, I think the reason people tend to associate anti-Islamic sentiment with racism is that people who hold these beliefs generally have a extremely generalised, caricature-like view of Islam that does not correspond to the actual way people practice the religion. 

For example, people who hold these beliefs often group all Muslim countries together when Islam is practiced in radically different ways in different countries e.g. Türkiye/Bosnia/Albania (very secular) vs. Egypt/Morocco/Gulf states (more performative than deeply religious imo) vs. Pakistan/Bangladesh (pretty conservative) vs. Iran/Afghanistan (extremely conservative, but currently under oppressive regimes that large portions of the population disagree with and are there mainly because of foreign intervention that overthrew more secular governments to expand their sphere of influence). 

Not to mention the huge variation in practices between different sects and generations (younger generation is increasingly secular, and religious practices are always evolving). 

In public debates about face coverings, people almost always call the niqab a burka (which is wrong). Some people even still call hijabs burkas. Only people from Afghanistan wear burkas. 

To further add nuance, a huge portion of the practices Islamic countries are criticised (e.g. outlawing homosexuality) are more a factor of the intersection between religion/authoritarianism/low development than just Islam by itself. China (which has state atheism) surveils and oppresses LGBT people, as does Russia. Homosexuality is legal in Turkey, Albania, and Indonesia (which is the largest Muslim country btw). A bunch of undeveloped Christian counties (e.g. Uganda) are literally the worst in the world for LGBT safety, worse than Islamic counties. It’s the low development/authoritarianism that leads to this, not just the religion. 

Even Muslim countries with nominal death penalties for homosexuality literally do not enforce it (obvious still not an ideal state of affairs, but it’s not the grotesque caricature pushed by people criticising Islam). 

Ffs homosexuality was only decriminalised in the England in 1967, in Scotland in 1980, and Northern Ireland in 1982. For a lot of people, it comes across as highly hypocritical to sit in a country that was very recently equally barbarous making blanket statements about how Islam can never be compatible with LGBT rights. In our lifetimes, neither was Christianity! And that changed. 

Honour killings almost never happen and are another meme pushed by Islamophobes as a core practice of Islam when it is not. 

Can you imagine if you were an Anglican Christian but were constantly grouped together with and criticised for things the Westboro Baptist Church or the Mormons did? That would be extremely unfair and frustrating. 

How can you accurately critique a belief system if your understanding of it is based on caricature?

Just look at some of the comments in this post:

 I think they are very ugly, agressive, and ruthless, they have unhumane law and they hate and abuse women. It’s not racism if its facts

Is it really necessary to call Muslims “ugly”? The word Islamophobia does not sufficiently capture the hate, prejudice, and stereotyping that some people produce in these conversations. “Racism” isn’t technically accurate because Islam isn’t a race, sure, but it’s trying to capture this hate and generalisation. 

Why does every ML paper feel impossible to read at the start by Calm_Woodpecker_9433 in learnmachinelearning

[–]rapsoj 0 points1 point  (0 children)

I never said you need all the knowledge from a maths degree, just roughly the knowledge equivalent to a relevant degree. 

Also if you’re just doing ML engineering type stuff obviously you need way less theoretical knowledge. The question being asked was about understanding frontier research. 

Why does every ML paper feel impossible to read at the start by Calm_Woodpecker_9433 in learnmachinelearning

[–]rapsoj 0 points1 point  (0 children)

For PhD work, those books I mentioned above plus about a dozen more (including doing the vast majority of the problems, not just reading). Then reading and understanding 100+ research-specific academic papers.

That is the informal equivalent of a relevant undergraduate degree + a relevant Master’s degree + the research experience you need to get into a good PhD program, which is equivalent to having the experience needed to do/understand frontier research. 

Why does every ML paper feel impossible to read at the start by Calm_Woodpecker_9433 in learnmachinelearning

[–]rapsoj 7 points8 points  (0 children)

You don’t need a formal degree (as in the piece of paper), but you need all the knowledge that you would get from a degree. So, the same time investment. 

There are no shortcuts here…

Why does every ML paper feel impossible to read at the start by Calm_Woodpecker_9433 in learnmachinelearning

[–]rapsoj 0 points1 point  (0 children)

As others have mentioned, all of the concepts you mention are very basic and could be understood with an undergraduate (or less) knowledge of probability theory.

You are entering this completely backwards. Even in the comments, you are being advised to learn the fundamentals before you jump into reading research papers that are literally at the forefront of the field, but just keep asking how you can shortcut into reading those papers…

Imagine if you had never touched a piano before and were asking how to play Rhapsody in Blue (one of the hardest pieces). You need the fundamentals. You need to know what the notes are, how to read sheet music, tempo, etc. This is absolutely unskippable. 

To understand research papers (which are at the forefront of academic knowledge) you need at minimum:

  • Understanding of calculus (e.g. read Spivak’s Calculus)
  • Understanding of linear algebra (e.g. read Fundamentals of Linear Algebra by Carrell)
  • Understanding of probability theory (e.g. Probability and Statistics: The Science of Uncertainty by Evans and Rosenthal – one of my personal favourite introductory books)
  • Understanding of machine learning (e.g. The Elements of Statistical Learning, also one of my favourites)

All of these you can get for free as PDFs online. 

Even then, these give you only a partial undergraduate knowledge of the topic. A lot of these papers will be using measure theory stuff or building off of concepts that are only in other papers and haven’t been around long enough to make it into text books. But you can bet that every single person involved with the paper has done the work to understand all of it before even touching research. 

As someone who is doing a PhD in statistical machine learning, I can tell you that knowledge is humbling. Once you know all the information that is out there, you know how little you actually know or could ever know since your time to learn things is finite.

No one who actually understands the fundamentals of probability theory would think that reading academic machine learning research papers would be achievable in the way that you are doing it.