tristanz

19 ms·

121.
by tristanz 13y ago
A problem with simulation in economics is that there is always a feeling that that simulation results are inferior to what could have been done if the writer was better at math. Let's say you derive some insight on heterogeneous agent
122.
by tristanz 13y ago
Anand and I built everything, including the choosing the colors of buttons. That's early stage startup life.
123.
by tristanz 13y ago
Scaling up from 10, 100, to 1000 cores is fast (3s per engine in parallel). However, something like 1000 cores would currently require spinning up new instances (1-2 minutes) if deployed in the cloud. The distributed filesystem is meant fo
124.
by tristanz 13y ago
The Python engine is IPython underneath the hood. Any code or visualizations that work in IPython notebooks should work in Sense. There is a difference though. In our experience, we've found that the notebook style development, with
125.
by tristanz 13y ago
Yup. It's just the two of us. So far. If anybody wants to join: tristan@senseplatform.com.
126.
by tristanz 13y ago
Yes, we're fans of how sharing and collaboration works on GitHub. The goal is to make Sense the center of gravity for data scientists the way GitHub is for developers. We're not trying to replicate GitHub's features. The cor
127.
by tristanz 13y ago
Yes. I'll also point our that Anand (apatil) was a core developer for PyMC. We have big plans around Bayesian computation on Sense.
128.
by tristanz 13y ago
You currently need an invitation code to register. We're giving these out slowly to make sure everything works smoothly.
129.
by tristanz 13y ago
Right now Sense is best for ad-hoc interactive analysis and batch/scheduled jobs. You can run long-running services that expose something like a REST endpoint, but we have plans to make exposing services much easier, so I'd proba
130.
by tristanz 13y ago
Sense cofounder here. We're just getting started, so feedback is welcome. Sense supports R, Python, JavaScript and SQL out of the box, but is fully extensible to new languages and tools: https://github.com/SensePlatform
131.
Show HN: Sense - A New Cloud Platform for Data Science and Big Data Analytics(senseplatform.com)
64 points by tristanz 13y ago|36 comments
132.
by tristanz 13y ago
I have no idea if 21% is correct, but on Amazon Chromebooks are 4 of the 5 top selling laptops. Something is going on. http://www.amazon.com/Best-Sellers-Electronics-Laptop-Comput...
133.
by tristanz 13y ago
It's unlikely to be much different than the recent Berkeley benchmarks, since they all ran on AWS: https://amplab.cs.berkeley.edu/benchmark/
134.
by tristanz 13y ago
This looks like the technology behind Prior Knowledge ( http://priorknowledge.com/ ), which is not surprising given that a lot of the same people are involved. Awesome that it's going open source. It will be interesting
135.
by tristanz 13y ago
DARPA and others think probabilistic programming: http://probabilistic-programming.org/wiki/Home You need to understand Bayesian statistics enough to understand this paper: http://www.stanford.edu/~ngoo
136.
by tristanz 13y ago
The overall GPA can still be used to rank, even at Harvard. The latin honors are fixed at top 5, 20, and 50 percent of graduating classes. I don't really care about grade inflation overall because I don't think more competition f
137.
by tristanz 13y ago
My experience was that it's relatively easy to stack rank Harvard undergraduates, but it often doesn't feel like it serves any educational purpose to do so. In the class I taught of 12, there were 10 that seemed like they deserved
138.
by tristanz 13y ago
This is an absolute work of art, if you take the time to digest what they've done. In order to articulate a model of cognition, they have implemented a probabilistic version of Scheme, that compiles to JavaScript, and that allows for
139.
Probabilistic Models of Cognition(probmods.org)
13 points by tristanz 13y ago|2 comments
140.
by tristanz 13y ago
All of it's definitely solvable, it's just harder than lots of Monte Carlo problems that are embarrassingly parallel.
141.
by tristanz 13y ago
This is the core calculation to all of Bayesian statistics, so it's used pretty much everywhere. Almost any time you try to compute p(unknown|data) you run into computational issues. It's a high dimensional integration problem t
142.
by tristanz 13y ago
Most Monte Carlo methods used to calculate Bayesian posterior distributions are iterative, you can't parallelize each draw since it depends on the previous draw. Moreover, each draw depends on a function of all the data, so if your dat
143.
by tristanz 13y ago
Astronomy and cosmology are not science?
144.
by tristanz 13y ago
The paper he cites is by David Romer, but it definitely does not say you should go for it 100% of the time. http://elsa.berkeley.edu/~dromer/papers/JPE_April06.pdf "Teams’ actual choices are dramatically more
145.
by tristanz 13y ago
I tend to agree with Ian that it's confusing to conflate probabilistic programming and libraries that support Bayesian inference. In PyMC variables represent random variables, but these variables can't be used with Python construc
146.
by tristanz 13y ago
Having started companies in both 2000 and 2012, I just don't think this is true. It was easy to put something in front of users in 2000 for less than $1000. We started with a $20/month shared host, PHP and MySql, and easily scal
147.
by tristanz 13y ago
Are these feature plans documented somewhere? Private networks, in the spirit of EC2 security groups or VPCs, would help simplify many distributed computing scenarios where securing services with passwords isn't an option.
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by tristanz 13y ago
Definitely a big need for this stuff. Nice job! Another approach that uses WebGL only and scales to billions of linked points at 50fps is the inMems project by the Stanford Visualization Group: http://vis.stanford.edu/paper
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by tristanz 13y ago
Some of the best advanced statistical visualizations I've seen are by Theory: http://theory.info/visuals .
150.
by tristanz 13y ago
Bayes Theorem can be implemented as an if statement: posterior = [] [observables, unknowns] = simulate_from_model(priors) if observables == observed posterior.push(unknowns) posterior now includes random draws from the poste

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