sbos’s gists

sbos / gist:5859327

Created June 25, 2013 15:18

build-error.log

	==> Using Homebrew-provided fortran compiler.
	This may be changed by setting the FC environment variable.
	==> Cloning https://github.com/JuliaLang/julia.git
	git --git-dir /Library/Caches/Homebrew/julia--git/.git status -s
	Updating /Library/Caches/Homebrew/julia--git
	git config remote.origin.url https://github.com/JuliaLang/julia.git
	git config remote.origin.fetch +refs/heads/master:refs/remotes/origin/master
	git fetch origin
	git checkout -f master
	Already on 'master'

sbos / HMM.jl

Created November 1, 2013 11:25

Hidden Markov Model in Julia

	module HMM

	using Distributions

	import Distributions.rand
	import Distributions.fit

	immutable HiddenMarkovModel{TP, K}
	theta::Vector{TP}
	A::Matrix{Float64}

sbos / gist:018955227319ead18529

Created November 10, 2014 06:31

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sbos / SVM.py

Last active October 19, 2022 04:06

Simple linear SVM using quadratic programming

	import numpy as np
	from cvxopt import matrix, spmatrix
	from cvxopt.solvers import qp
	from cvxopt import solvers

	class LinearSVM():
	def __init__(self, C):
	self.C = C

	def fit(self, data, labels):

sbos / cgt_simplification_bug.py

Created October 20, 2015 19:36

	import cgt
	import cgt.nn as nn
	import numpy as np
	from scipy.stats import norm

	def gaussian_density(x, mu, sigma):
	return cgt.exp(-cgt.square(x - mu) / 2 / cgt.square(sigma)) \
	/ cgt.sqrt(2 * np.pi) / sigma

	var_mu = nn.parameter(np.array(0.5))

sbos / cgt_memory.py

Last active October 21, 2015 21:27

	import cgt
	import cgt.nn as nn
	import numpy as np
	from scipy.stats import norm

	def gaussian_density(x, mu, sigma):
	return cgt.exp(-cgt.square(x - mu) / 2 / cgt.square(sigma)) \
	/ cgt.sqrt(2 * np.pi) / sigma

	var_mu = nn.parameter(np.array(0.5))

sbos / random_bug.py

Created October 24, 2015 05:01

	import cgt
	import cgt.nn as nn
	import numpy as np

	batch = 5000

	mean = 0.
	for i in xrange(batch):
	mean += (cgt.randn() - mean) / (i+1)

sbos / debug_th.py

Created November 26, 2015 13:30

	import theano as th
	import theano.tensor as T
	import lasagne
	import numpy as np
	from theano.tensor.shared_randomstreams import RandomStreams
	from lasagne.nonlinearities import tanh
	import matplotlib.pyplot as plt
	import sys

	# change to True and see what happens

sbos / baseline.ipynb

Created December 15, 2015 04:03

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sbos / adagram_export.jl

Last active October 22, 2016 18:04

	function write_word2vec(path::AbstractString, vm::VectorModel, dict::Dictionary)
	fout = open(path, "w")
	sense_prob = zeros(T(vm))
	write(fout, "$(V(vm)) $(T(vm)) $(M(vm))\n")
	for v in 1:V(vm)
	write(fout, "$(dict.id2word[v])\n")
	expected_pi!(sense_prob, vm, v)
	for k in 1:T(vm)
	if sense_prob[k] < 1e-3 continue end
	write(fout, "$k $(sense_prob[k]) ")

Sergey Bartunov sbos