Rosaria Silipo

In Praise of the Autoencoder

When you consider all the machine learning (ML) algorithms, you’ll find there is a subset of very pragmatic ones: neural networks. They usually require no statistical hypothesis and no specific data preparation except for normalization. The power of each network lies in its architecture,...

Is Deep Learning Just Neural Networks on Steroids?

Takeaway: Is "deep learning" just another name for advanced neural networks, or is there more to it than that? We take a look at recent advances in deep learning as well as neural networks. The Skeptics Club If you, like me, belong to the skeptics…

Can You Guess a Song by Its Word Cloud?

At any important political or social event, the aftermath of the keynote speech is often entrusted to a Word Cloud. The large size of the most frequently repeated words supposedly conveys the central topics of the speech. Is it really so? Can we really...

Text Encoding: A Review

The key to perform any text mining operation, such as topic detection or sentiment analysis, is to transform words into numbers, sequences of words into sequences of numbers. Once we have numbers, we are back in the well-known game of data analytics, where machine...

What’s in a Name? Artificial Intelligence or Data Science?

via KNIME If you are like me, there is a good chance that you are confused as well about the most recent terminology to use in the field of data science … pardon, artificial intelligence … no, I mean data science. No, I mean...

Data Dimensionality Reduction in the Age of Machine Learning

Machine Learning is all the rage as companies try to make sense of the mountains of data they are collecting. Data is everywhere and proliferating at unprecedented speed. But, more data is not always better. In fact, large amounts of data can not only...

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