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View chana_masala.md

Chana Masala

Prep time: 15 mins Cooking time: 40-45 mins Serves: 4

Ingredients:

  • 2 Onions - sliced finely
  • 4 cloves of garlic - chopped finely (or crushed)
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mobeets / random_cribbage.py
Created Jun 17, 2018
estimating what percentage of cribbage games are winnable by random play
View random_cribbage.py
import itertools
import numpy as np
# https://github.com/relsqui/pydeck
from pydeck import standard, cribbage
CARDS_PER_DEAL = 6
CARDS_PER_HAND = 4
POINTS_TO_WIN = 121
VERBOSE = False
View example.csv
0.620713 0.463101 0.869851 0.610158 0.702451 0.767094
0.797397 0.441206 0.753544 0.679309 0.524256 0.752844
0.58715 0.137027 0.938175 0.590607 0.840056 0.652926
0.176337 0.909013 0.356048 0.306722 0.134125 0.669478
0.790946 0.155954 0.173121 0.310723 0.989607 0.294101
0.620713 0.463101 0.869851 0.610158 0.702451 0.767094
0.797397 0.441206 0.753544 0.679309 0.524256 0.752844
0.58715 0.137027 0.938175 0.590607 0.840056 0.652926
0.176337 0.909013 0.356048 0.306722 0.134125 0.669478
0.790946 0.155954 0.173121 0.310723 0.989607 0.294101
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mobeets / ferguson.md
Last active Aug 29, 2015
questions to ask next time someone makes definitive or latently racist comments about Ferguson
View ferguson.md

The following questions can be asked of people (e.g., family members) who somehow manage to form simple opinions about very complex events.

Q1. Where have you learned about the event? First-hand? Or second-hand, through the media?

Q2. Have you ever sought out news about the event?

For example, have you ever had a question about the event and then sought an answer yourself, or do you learn about it as presented via friends and/or the media?

Q3. Have you tried your best to consider the perspective of both sides involved? If so, is there a benefit to you personally in arriving at a definitive opinion?

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mobeets / CMU_Pitt.md
Last active Aug 29, 2015
neuroscience/statistics programs
View CMU_Pitt.md

Programs

tl;dr: 1) apply to PhD in: stats/neuro, 2) stats; 3) apply to CNBC program

PhD in Statistics and Neural Computation: This degree is aimed at students who want to join the PNC program, while also specializing in statistics.

Ph.D. Program in Neural Computation: a graduate training program in computational neuroscience for students seeking training in the application of quantitative approaches to the study of the brain.

CNBC Grad Training Program: to be admitted to the CNBC Training Program, students must have been accepted into one of the affiliated doctoral programs at either the University of Pittsburgh or Carnegie Mellon. For students applying from outside the two universities, applications to the doctoral program and the CNBC program may be submitted simultaneously. n.b. not a degree-granting program but I still need to apply

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mobeets / journal.md
Last active Aug 29, 2015
journal management ideas
View journal.md

Workflow

  1. Command line jrn creates file (from template if desired) for specified day, date range, file format
  2. Daily builds
  • inputs: *.rtf, *.txt, *.md, *.html, *.png. *.jpeg
  • output: *.md
  • dirs: Journal/ -> _posts/
  • update _data/counts.json
  1. Jekyll template for viewing/searching posts
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mobeets / outline.md
Last active Aug 29, 2015
Using Gibbs to fit state-space model with point process observations
View outline.md

Paper: Markov Chain Monte Carlo Methods for State-Space Models with Point Process Observations

Model

  • P(Y_k | X_k, mu, beta) ~ Poisson(lambda_k)
  • lambda_k = exp(mu + beta*X_k)
  • x_k = px_{k-1} + alphaI_k + e_k

where e_k normally distributed with zero mean and known variance; also, I, alpha, and beta are known.

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mobeets / ffbs.md
Last active Aug 29, 2015
Gibbs sampling to estimate AR(1) model parameters
View ffbs.md

Gibbs sampling to estimate AR(1) model parameters.

Source: SSC 389: AR(1) + noise

Definitions

  • Xt is hidden state at time t
  • Yt is observed state at time t
  • Dt is information known at time t, i.e. {Y1, ..., Yt}
  • T is length of X, Y, D
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mobeets / snr.md
Last active Aug 29, 2015
Q: Why does calculating SNR involve squaring the signal strength?
View snr.md

Definitions

SNR = Power(signal) / Power(noise)

Power(x(t)) = average Energy(x(t)) over all t

Energy(x(t)) = the area under |x(t)|^2

(Energy/power involve squaring the signal because you are interested in the magnitude of the signal and not just its amplitude. That's it.)