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Texthero is a python package to work with text data efficiently. It empowers NLP developers with a tool to quickly understand any text-based dataset and it provides a solid pipeline to clean and represent text data, from zero to hero.
STUMPY is a powerful and scalable Python library for modern time series analysis and, at its core, efficiently computes something called a matrix profile. The goal of this multi-part series is to explain what the matrix profile is and how you can start leveraging STUMPY for all of your modern time series data mining tasks!
Weather forecasting is a tricky problem. Traditionally, it has been done by manually modelling weather dynamics using differential equations, but this approach is highly dependent on us getting the equations right. To avoid this problem, we can use machine learning to directly predict the weather, which let’s us make predictions without modelling the dynamics. However, this approach requires huge amounts of data to reach good performance. Fortunately, there is a middle ground: What if we instead use machine learning to model the dynamics of the weather?
After 10ish years of second-hand shopping, I've started to ask myself a lot of questions about the clothes I've been buying, like, "Did someone die in this?" or, "Have thrift stores always been this pricy?" (the answer to the former being, "yeah, probably"). In the absense of any conclusive answers, I tried to get the data myself.
For the last 20 years, machine learning has been about one question: Can we train a model to do something?