Machine Learning

Developing a Web Application for a Machine Learning Model

This post describes developing a web application for a machine learning model and deploying it so that it can be accessed by anyone. The web application is available at: https://arrear-model.herokuapp.com/ The process of deployment consists of transferring all flask application files from a local computer to the web server. Once completed the web application can be visited by anyone through…

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Machine Learning, Predictive Analysis

Guide for Linear Regression using Python – Part 2

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 true effect of X on…

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Predicting NBA winners with Decision Trees and Random Forests in Scikit-learn
Machine Learning, Predictive Analysis, scikit-learn

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

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 1 in Canada). The data…

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Machine Learning Algorithms
Data Analysis Resources, Machine Learning, Predictive Analysis

10 groups of Machine Learning Algorithms

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 of the dependent variable. It…

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countvectorizer sklearn example
Data Analysis Resources, Machine Learning, scikit-learn

Countvectorizer sklearn example

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 buffet… Cine there got amore…

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