Pandas is a popular library for data analysis built on top of the Python programming language. Pandas can be though as a digital toolbox that holds various tools for working with data. Pandas pairs well with other libraries for statistics, natural language processing, machine learning, visualization, and more. Pandas is…

Sequence-to-sequence (S2S) models are a special case of a general family of models called encoder–decoder models. An encoder–decoder model is a composition of two models, an “encoder” and a “decoder,” that are typically jointly trained. The encoder model takes an input and produces an encoding or a representation (ϕ) of…

Sequence prediction tasks require us to label each item of a sequence. Such tasks are common in natural language processing. Some examples include language modeling. in which we predict the next word given a sequence of words at each step; part-of-speech tagging, in which we predict the grammatical part of…

A sequence is an ordered collection of items. Traditional machine learning assumes data points to be independently and identically distributed (IID), but in many situations, like with language, speech, and time-series data, one data item depends on the items that precede or follow it. Such data is also called sequence…

In this section we discussed feature engineering techniques using neural networks, such as word-embeddings, character-embeddings. The advantage of using embedding based features is that they create a dense, low-dimensional feature representation instead of the sparse, high-dimensional structure of bag of words/TFIDF and other such features. …

Duy Anh Nguyen

AI Researcher - NLP Practitioner

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