FastText — a solution for classification with a large number of labels
Fig 0. Illustration of “choice”
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Category: Python
Python tutorials
Tl;dr —I built a web app that summarizes search articles
Because your time is important.
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Diving into BERT
Advance NLP topics like BERT, Transformers are now getting very popular. So, here is my exploration about the topic BERT. But to understand BERT, we need to have an idea of Transformers.
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Beating the House for Dummies (who know Python)
Capitalizing on online sports betting legalization, by using promotional arbitrage, to make over $13,000 Disclaimers: Please do not gamble [1]. This article is not meant to promote gambling. This article is written about a hypothetical scenario and is meant for educational purposes only. More disclaimers
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Wordcloud con Spacy
Búsqueda de verbos y sustantivos con Spacy
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Minimax in Python: Learn How to Lose the Game of Nim
You’ve gotten to know the steps of the minimax algorithm. In this section, you’ll implement minimax in Python. You’ll start by tailoring the algorithm directly to the game of Simple-Nim. Later, you’ll refactor your code to separate the core of the algorithm from the rules of the game, such that you can later apply your minimax code to other games. Implement a Nim-Specific Minimax Algorithm Consider the same example as in the previous section: it’s Maximillian’s turn, and there are […]
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FAST TEXT ALGORITHM
FastText is a lightweight, open-source framework that enables users to learn text representations and classifiers. It runs on common, generic hardware. This model may be used to create an unsupervised or supervised learning technique for obtaining word vector representations. This module has acquired a lot of interest in the NLP community and might be a viable alternative to the genism package, which includes Word Vectors and other features. FastText differs in that word vectors, also known as word2vec, take […]
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