Guide for Linear Regression using Python – Part 2

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Guide for Linear Regression using Python – Part 2 This blog is the continuation of guide for linear regression using Python from this post. There must be no correlation among independent variables. Multicollinearity is the presence of correlation in independent variables. If variables are correlated, it becomes extremely difficult for the model to determine the […]



Predicting NBA winners with Decision Trees and Random Forests in Scikit-learn

Predicting NBA winners with Decision Trees and Random Forests in Scikit-learn

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In this blog, we will be predicting NBA winners with Decision Trees and Random Forests in Scikit-learn.The National Basketball Association (NBA) is the major men’s professional basketball league in North America and is widely considered to be the premier men’s professional basketball league in the world. It has 30 teams (29 in the United States and […]



Machine Learning Algorithms

10 groups of Machine Learning Algorithms

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In this article, I grouped some of the popular machine learning algorithms either by learning or problem type. There is a brief description of how these algorithms work and their potential use case. Regression How it works: A regression uses the historical relationship between an independent and a dependent variable to predict the future values […]



countvectorizer sklearn example

Countvectorizer sklearn example

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This countvectorizer sklearn example is from Pycon Dublin 2016. For further information please visit this link. The dataset is from UCI. In [2]: messages = [line.rstrip() for line in open(‘smsspamcollection/SMSSpamCollection’)] In [3]: print (len(messages)) 5574 In [5]: for num,message in enumerate(messages[:10]): print(num,message) print (‘\n’) 0 ham Go until jurong point, crazy.. Available only in bugis n great world la e […]