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Working Analytics | Building analytics experience and skills

Building analytics experience and skills. Data Smart, Ch3, Classifying Tweets using Naive Bayes. 29 May 2015, 10:00 am. In chapter 3 of the book, Data Smart. Chief data scientist at Mailchimp. The author develops a Naive Bayes classifier in Excel to determine whether tweets containing the word ‘mandrill’ are related to Mailchimps. S Mandrill email-transaction app or not. Whereas the author used Excel, we choose to use R’s text mining package, tm. The book, Machine Learning for Hackers. Classify the tweet...

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Working Analytics | Building analytics experience and skills | workinganalytics.com Reviews

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Building analytics experience and skills. Data Smart, Ch3, Classifying Tweets using Naive Bayes. 29 May 2015, 10:00 am. In chapter 3 of the book, Data Smart. Chief data scientist at Mailchimp. The author develops a Naive Bayes classifier in Excel to determine whether tweets containing the word ‘mandrill’ are related to Mailchimps. S Mandrill email-transaction app or not. Whereas the author used Excel, we choose to use R’s text mining package, tm. The book, Machine Learning for Hackers. Classify the tweet...

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Working Analytics | Building analytics experience and skills | workinganalytics.com Reviews

https://workinganalytics.com

Building analytics experience and skills. Data Smart, Ch3, Classifying Tweets using Naive Bayes. 29 May 2015, 10:00 am. In chapter 3 of the book, Data Smart. Chief data scientist at Mailchimp. The author develops a Naive Bayes classifier in Excel to determine whether tweets containing the word ‘mandrill’ are related to Mailchimps. S Mandrill email-transaction app or not. Whereas the author used Excel, we choose to use R’s text mining package, tm. The book, Machine Learning for Hackers. Classify the tweet...

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Pricing Wholesale Milk Contracts – Working Analytics

http://workinganalytics.com/case-studies-2

Building analytics experience and skills. Pricing Wholesale Milk Contracts. We were asked by a major dairy exporter to investigate and propose analytics techniques to help improve the pricing of their wholesale dairy contracts. Milk is a vital food resource and milk production is a huge industry. Global milk production is around 700 million tonnes, annually. What was the problem? Fig 1 Price swings in class III Milk Prices during the period 1980 – 2013. We started by defining our ideal dataset as:. Since...

2

‘R’ – Working Analytics

http://workinganalytics.com/tag/r

Building analytics experience and skills. Archive of posts tagged ‘R’. Data Smart, Ch3, Classifying Tweets using Naive Bayes. 29 May 2015, 10:00 am. Executive Summary In chapter 3 of the book, Data Smart, by John Foreman, chief data scientist at Mailchimp, the author develops a Naive Bayes classifier in Excel to determine whether tweets containing the word ‘mandrill’ are related to Mailchimps’s Mandrill email-transaction app or not. Whereas the author used Excel, we choose to use …. 7 May 2015, 3:45 pm.

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Machine Learning – Working Analytics

http://workinganalytics.com/tag/machine-learning

Building analytics experience and skills. Archive of posts tagged Machine Learning. Data Smart, Ch3, Classifying Tweets using Naive Bayes. 29 May 2015, 10:00 am. Executive Summary In chapter 3 of the book, Data Smart, by John Foreman, chief data scientist at Mailchimp, the author develops a Naive Bayes classifier in Excel to determine whether tweets containing the word ‘mandrill’ are related to Mailchimps’s Mandrill email-transaction app or not. Whereas the author used Excel, we choose to use …. Executiv...

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Data Smart, Ch2, Customer Segmentation With R Using K-Medians Clustering – Working Analytics

http://workinganalytics.com/data-smart-ch2-customer-segmentation-with-r-using-k-medians-clustering-2

Building analytics experience and skills. Data Smart, Ch2, Customer Segmentation With R Using K-Medians Clustering. 1 May 2015, 10:50 am. This is a walk-through of a customer segmentation process using R’s skmeans. Package to perform k-medians clustering. The dataset examined is that used in chapter 2 of John Foreman. 8216;s book, Data Smart. This walk-through includes R function calls to calculate silhouette. Values as measures of segmentation effectiveness. A note on the silhouette. An excellent tool f...

5

Connections – Working Analytics

http://workinganalytics.com/connections

Building analytics experience and skills. For older Meetup reports, please scroll down. Big Data = Big Business Meetup, May 29th, 2014, Sammamish, WA. The main speaker this evening, Rolfe Lindberg, of Double Down Interactive. Gave the most impressive and convincing presentation I have seen on BI systems this year. Underlying the story of a young company’s success and a BI function’s progression, is a tale of great execution. Rolfe’s presentation is available here: BI Buildout. The next major advance was ...

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Working Analytics | Building analytics experience and skills

Building analytics experience and skills. Data Smart, Ch3, Classifying Tweets using Naive Bayes. 29 May 2015, 10:00 am. In chapter 3 of the book, Data Smart. Chief data scientist at Mailchimp. The author develops a Naive Bayes classifier in Excel to determine whether tweets containing the word ‘mandrill’ are related to Mailchimps. S Mandrill email-transaction app or not. Whereas the author used Excel, we choose to use R’s text mining package, tm. The book, Machine Learning for Hackers. Classify the tweet...

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working – and cooking – girl | sobre uma menina de futuro

Working and cooking girl. Sobre uma menina de futuro. 11 de agosto de 2011. So much of life is just fixing food. 8 de fevereiro de 2011. My friend emailed me this article: http:/ tv.nytimes.com/2001/09/19/dining/19COOK.html. It hit me: I meet people and watch them doing so much with their lives that I forget that I am also doing important things. And in the rush to get more things done, I end up fixing food. You know what I mean? I’m stoping by the market on my way home. 😉. 23 de novembro de 2010. Vamos...

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Working and Learning | The home of the Working and Learning Newsletter – published jointly by NoShortageOfWork.com and Q4Colleges.com

Email Address * (*=Required). Free copy of “Don’t Do Anything that Can Kill You – Yet Another College Guide” by Scott White. 8212;—————————————. Is a joint publication of Questions for Colleges ( Q4Colleges.com. And No Shortage of Work. Which are non-commercial projects dedicated to questions of higher education and work life respectively. Here is more information about our current free offers:. 8212;———————————. Don’t Do Anything that Can Kill You. He says, “The common thread among the students ha...

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Working and learning in Science ¡Cientifícate! (1º y 2º ESO)

Working and learning in Science ¡Cientifícate! 1º y 2º ESO). Blog del Departamento de Ciencias de la Naturaleza (Biología y Geología) del Colegio María Inmaculada de Madrid. Pictures / Galería de imágenes. Lunes, 9 de mayo de 2016. Nacimiento de una abeja. Una abeja obrera tarda 21 días en nacer desde que se ha depositado el huevo. En estos aproximadamente 60 segundos, podemos ver como se va desarrollando dicho nacimiento. Enviar por correo electrónico. Etiquetas: Ciencias de la Naturaleza 1º ESO. Aquí o...