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In a previous post, I have provided a discussion of model stacking, a popular approach in data science competitions for boosting predictive performance. Since then, the post has attracted some attention, so I have decided to put together a Python package which provides a simple API to stack models with minimal effort.
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Introduction Feature selection and engineering are the most important factors which affect the success of predictive modeling. This remains true … More
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Time-series data arise in many fields including finance, signal processing, speech recognition and medicine. A standard approach to time-series problems … More
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It is no news to anyone that applications of machine learning span a vast range of fields, from artificial intelligence … More
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In this blog post I will discuss web scraping using R. As an example, I will consider scraping data from … More
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In this blog post, I will discuss feature engineering using the Tidyverse collection of libraries. Feature engineering is crucial for … More
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There are many great tutorials on neural networks that one can find online nowadays. Simply searching for the words “Neural Network” … More
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Recently, I have been working on the Neural Networks for Machine Learning course offered by Coursera and taught by Geoffrey Hinton. … More
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If you have ever competed in a Kaggle competition, you are probably familiar with the use of combining different predictive models … More