Ulul ululh

ululh / index.html

Last active May 15, 2016 10:18 — forked from nautat/index.html

Nested tables from json

	<!DOCTYPE html>
	<meta charset="utf-8">
	<style type="text/css">
	table {
	font-family: "Helvetica", "Lucida Sans", "Lucida Sans Unicode", "Luxi Sans", Tahoma, sans-serif;
	box-shadow: 1px 1px 10px rgba(0,0,0,0.5);
	border-collapse: collapse;
	border-spacing: 0;
	}
	table {

ululh / LDAfit.py

Last active May 22, 2021 01:27

LDA (Latent Dirichlet Allocation) fitting with python scikit-learn

	# derived from http://scikit-learn.org/stable/auto_examples/applications/topics_extraction_with_nmf_lda.html
	# explanations are located there : https://www.linkedin.com/pulse/dissociating-training-predicting-latent-dirichlet-lucien-tardres

	from sklearn.feature_extraction.text import CountVectorizer
	from sklearn.decomposition import LatentDirichletAllocation
	import pickle

	n_features = 50
	n_topics = 2

ululh / LDApredict.py

Last active February 1, 2023 09:32

LDA (Latent Dirichlet Allocation) predicting with python scikit-learn

	# derived from http://scikit-learn.org/stable/auto_examples/applications/topics_extraction_with_nmf_lda.html
	# explanations are located there : https://www.linkedin.com/pulse/dissociating-training-predicting-latent-dirichlet-lucien-tardres

	from sklearn.feature_extraction.text import CountVectorizer
	from sklearn.decomposition import LatentDirichletAllocation
	import pickle

	# create a blank model
	lda = LatentDirichletAllocation()