Multidimensional multi-sensor time-series data analysis framework

Multidimensional multi-sensor time-series data analysis framework. In this blog post, I will take you through my package “msda” useful for time-series sensor data analysis. A quick introduction about time-series data is also provided. The demo notebook can be found on here. One of the specific use case applications focused on “Unsupervised Feature Selection” using the package can be found in the blog post here.

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GPT-2 vs GPT-3: The OpenAI Showdown

Woman at a blackboard

GPT-2 vs GPT-3: The OpenAI Showdown. The Generative Pre-Trained Transformer (GPT) is an innovation in the Natural Language Processing (NLP) space developed by OpenAI. These models are known to be the most advanced of its kind and can even be dangerous in the wrong hands. It is an unsupervised generative model which means that it takes an input such as a sentence and tries to generate an appropriate response, and the data used for its training is not labelled.

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My machine learning model does not learn. What should I do?

If you work with data in general, and machine learning algorithms in particular, you might be familiar with that feeling of frustration when a model really does not want to learn the task at hand. You have tried it all, but the accuracy metric just won’t rise. What next? Where is the problem? Is this an unsolvable task or is there a solution somewhere you’re not aware of?

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Adversarial attacks on explainable AI

There are various adversarial attacks on machine learning models; hence, ways of defending, e.g. by using Explainable AI methods. Nowadays, attacks on model explanations come to light, so does the defense to such adversary. Here, we introduce fundamental concepts related to the domain. When considering an explanation as a function of model and data, there is a possibility to change one of these variables to achieve a different result.

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Essential math for Data Science: Introduction to matrices and the matrix product

As you saw in Essential Math for Data Science, vectors are a useful way to store and manipulate data. You can represent them geometrically as arrows, or as arrays of numbers (the coordinates of their ending points). However, it can be helpful to create more complicated data structures – and that is where matrices need to be introduced.

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Getting started with 5 essential Natural Language Processing libraries

This article is an overview of how to get started with 5 popular Python NLP libraries, from those for linguistic data visualization, to data preprocessing, to multi-task functionality, to state of the art language modeling, and beyond.

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Vision Transformers: Natural Language Processing (NLP) increases efficiency and model generality

Vision Transformers: Natural Language Processing (NLP) Increases Efficiency and Model Generality. Why do we hear so little about transformer models applied to computer vision tasks? What about attention in computer vision networks? Transformers Are for Natural Language Processing (NLP), Right?

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