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NTDS’17 demo 3: Numpy

source Similar Notebooks ipython notebook 3 numpy gistfile1 txt science numpy french whats new numpy 1 8 Copyright © Code Fetcher 2022 Hermina Petric Maretic, EPFL LTS4 NumPy is the fundamental package for scientific computing with Python. It contains among other things: a powerful N-dimensional array object sophisticated (broadcasting) functions tools for integrating C/C++ and… Continue reading NTDS’17 demo 3: Numpy

5.- Listas y Tuplas

Data too large for file format source Similar Notebooks 13 aprendizaje de m c3 a1quina 7 arreglos con numpy 8 cadenas 1 programaci c3 b3n orientada a objetos checkpoint 6 diccionarios y conjuntos 4 funciones 8 1 de excel a python 3 control y desarrollo de programas 11 recursi c3 b3n iteraci c3 b3n busqueda… Continue reading 5.- Listas y Tuplas

Introduction to Linear Regression

Adapted from Chapter 3 of An Introduction to Statistical Learning continuous categorical supervised regression classification unsupervised dimension reduction clustering Motivation Why are we learning linear regression? widely used runs fast easy to use (not a lot of tuning required) highly interpretable basis for many other methods Libraries Will be using Statsmodels for teaching purposes since… Continue reading Introduction to Linear Regression

Analyzing police daily activity logs

Introduction How many? When? Introduction The Sacramento Police Department daily activity logs website was always the first I visited when I worked the early morning crime shifts at the Sacramento Bee. A public relations officer updated it every morning with a fairly well-standardized list of notable incidents the department responded to the day before, and… Continue reading Analyzing police daily activity logs

word2vec visualization

using vis.py ipython notebook version: https://gist.github.com/chezou/3899461aa550f73854a1 original vis.py https://github.com/nishio/mycorpus In [1]: import visword2vec # 単語で作ったモデル vis = visword2vec.visWord2Vec(“recipe_steps.bin”) # フレーズで作ったモデル vis_phrase = visword2vec.visWord2Vec(“recipe_steps-phrase.bin”) loading loaded loading loaded In [2]: def plot_both(word): vis.plot(word) vis_phrase.plot(word) In [3]: plot_both(‘チョコ’) [ 0.21099427 0.11427726] [ 0.19734898 0.13841781] In [4]: vis_phrase.plot(‘義理_チョコ’) [ 0.16700684 0.1221358 ] In [5]: plot_both(‘義理’) [ 0.17986007 0.14094272] [ 0.248188 0.16636363] In [6]: plot_both(‘あつあつ’)… Continue reading word2vec visualization