Building Recurrent Neural Networks in Tensorflow

Posted on 1 CommentPosted in Classification, Machine Learning, recurrent neural networks, tensorflow

Introduction In the previous blog posts we have seen how we can build Convolutional Neural Networks in Tensorflow and also how we can use Stochastic Signal Analysis techniques to classify signals and time-series. In this blog post, lets have a look and see how we can build Recurrent Neural Networks in Tensorflow and use them to […]

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Machine Learning with Signal Processing Techniques

Posted on 7 CommentsPosted in Classification, Machine Learning, scikit-learn, Stochastic signal analysis

Introduction Stochastic Signal Analysis is a field of science concerned with the processing, modification and analysis of (stochastic) signals. Anyone with a background in Physics or Engineering knows to some degree about signal analysis techniques, what these technique are and how they can be used to analyze, model and classify signals. Data Scientists coming from […]

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The Perceptron

Posted on 10 CommentsPosted in Classification, Machine Learning

1. Introduction Most tasks in Machine Learning can be reduced to classification tasks. For example, we have a medical dataset and we want to classify who has diabetes (positive class) and who doesn’t (negative class). We have a dataset from the financial world and want to know which customers will default on their credit (positive […]

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Regression, Logistic Regression and Maximum Entropy part 2 (code + examples)

Posted on 9 CommentsPosted in Classification, Sentiment Analytics

update: The Python code for Logistic Regression can be forked/cloned from my Git repository. It is also available on PyPi. The relevant information in the blog-posts about Linear and Logistic Regression are also available as a Jupyter Notebook on my Git repository.   Introduction In the previous blog we have seen the theory and mathematics behind the […]

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Regression, Logistic Regression and Maximum Entropy

Posted on 4 CommentsPosted in Classification, Machine Learning, Sentiment Analytics

update: The Python code for Logistic Regression can be forked/cloned from my Git repository. It is also available on PyPi. The relevant information in the blog-posts about Linear and Logistic Regression are also available as a Jupyter Notebook on my Git repository. 1. Introduction One of the most important tasks in Machine Learning are the Classification tasks […]

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Sentiment Analysis with the Naive Bayes Classifier

Posted on 13 CommentsPosted in Machine Learning, Sentiment Analytics

From the introductionary blog we know that the Naive Bayes Classifier is based on the bag-of-words model. With the bag-of-words model we check which word of the text-document appears in a positive-words-list or a negative-words-list. If the word appears in a positive-words-list the total score of the text is updated with +1 and vice versa. […]

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Sentiment Analysis with bag-of-words

Posted on 9 CommentsPosted in Machine Learning, Sentiment Analytics

update: the dataset containing the book-reviews of Amazon.com has been added to the UCI Machine Learning repository. Introduction: In my previous post I have explained the Theory behind three of the most popular Text Classification methods (Naive Bayes, Maximum Entropy and Support Vector Machines) and told you that I will use these Classifiers for the automatic […]

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Text Classification and Sentiment Analysis

Posted on 10 CommentsPosted in Machine Learning, Sentiment Analytics

Introduction: Natural Language Processing (NLP) is a vast area of Computer Science that is concerned with the interaction between Computers and Human Language[1]. Within NLP many tasks are – or can be reformulated as – classification tasks. In classification tasks we are trying to produce a classification function which can give the correlation between a […]

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