dataminingcrm.com
Category: Technical - Data Mining: Practical Machine Learning Techniques for CRM
http://www.dataminingcrm.com/home/category/technical
Data Mining: Practical Machine Learning Techniques for CRM. Getting Started: ARFF Files. Data mining platforms convert several data sources into a common data structure that allows an ecosystem of plug-in components to emerge and "speak a common language". In Weka machine learning, this common file format is called Attribute-Relation File Format. Or ARFF for short. Converting Salesforce Objects to ARFF: SObj2ARFF. Download and Build SObj2ARFF. Workspace/weka ./build.sh. Config file name/value pairs.
dataminingcrm.com
Category: Financial - Data Mining: Practical Machine Learning Techniques for CRM
http://www.dataminingcrm.com/home/category/financial
Data Mining: Practical Machine Learning Techniques for CRM. Classifying Machine Learning Problems. When approaching CRM analysis using machine learning, it helps to first understand and categorize the problem. Each of the quadrants in the diagram below has it's own unique set of data collection and processing requirements. Problems result in labeling data. Problems result in making a numeric prediction, such as a probability. Opportunity Win/Loss (Batch Classification):. A call center may make make predi...
cs.waikato.ac.nz
Weka 3 - Data Mining with Open Source Machine Learning Software in Java
http://www.cs.waikato.ac.nz/~ml/weka/index.html
Machine Learning Group at the University of Waikato. Weka 3: Data Mining Software in Java. Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes. And the bird sounds like this.
tizianacapozzoli.it
Corsi - Tiziana Capozzoli
http://tizianacapozzoli.it/corsi
Coursera Machine Learning 2014. Protected by WP Anti Spam. Se ascolto, dimentico. Se vedo, ricordo. Se faccio, imparo. Social media manager per Figmenta. Social Media Manager per NetEnjoy. Social Media Analyst per Blogmeter. Social Media Manager @ Ben&Jerry. Tensorflow: il machine learning di Google diventa open source. Che cos’è il machine learning? Social media manager per Figmenta. How much information in data? Di come Facebook rese famoso un villaggio di 76 abitanti. Social Media Manager per NetEnjoy.
cs.waikato.ac.nz
Weka 3 - Data Mining with Open Source Machine Learning Software in Java
http://www.cs.waikato.ac.nz/ml/weka/index.html
Machine Learning Group at the University of Waikato. Weka 3: Data Mining Software in Java. Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes. And the bird sounds like this.
wekamooc.blogspot.com
Data Mining with Weka: March 2016
http://wekamooc.blogspot.com/2016_03_01_archive.html
Data Mining with Weka. MOOCs from the home of Weka: University of Waikato, New Zealand. Thursday, 3 March 2016. Both "Data Mining with Weka" and "More Data Mining with Weka" are now available on a. Self-paced basis. All the material, activities and assessments are available now until 15th April 2016 at:. Https:/ weka.waikato.ac.nz/. We are not providing any tutorial, help or assistance during this session. Also, we will not generate any Statements of Completion until after 15th April. Links to this post.
cs.waikato.ac.nz
Weka 3 - Data Mining with Open Source Machine Learning Software in Java
http://www.cs.waikato.ac.nz/ml/weka
Machine Learning Group at the University of Waikato. Weka 3: Data Mining Software in Java. Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes. And the bird sounds like this.
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