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Step by step guide with full implementation in Python

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There are several approaches to perform automatic text summarization. It can be done with supervised or unsupervised learning, with deep or only machine learning. And inside these categories, there are a wide variety of methods.

In terms of types of summaries, there are two — extractive and abstractive. The program…

TF-IDF: understand this technique used in search engines and other machine learning applications

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You may have encountered this acronym if you’re studying Machine Learning (ML) and specifically Natural Language Processing (NLP). “TF-IDF”. I keep finding it in every research paper I read about automatic text summarization.

“TF-IDF.. again!” is always my thinking.

To recap a key concept. In NLP, the text terms/words are…

Introduction to sentence segmentation, tokenization, stop word removal, stemming, and lemmatization

Typewriter keyboard
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For context, imagine the implementation of a chatbot or an automatic text summarizer.

The algorithm must find the correlation between words and sentences and extract knowledge from the data — it’s a complex and time-consuming task for computers.

Because it’s a complex operation, the program mustn’t spend time processing parts…

Including hands-on calculations using the cosine similarity formula

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It’s often the case in machine learning that you need to compare data and analyze how similar they are.

For instance, in automatic text summarization, during training, you need to identify which sentences from the original document are similar to the sentences in the reference summary. …

A beginner’s guide on the two types of learning

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Many solutions in Machine Learning (ML) are implemented using either Unsupervised or Supervised learning algorithms. In this article, I cover the basics of each approach—the definition and application examples.


Supervised learning is when the program is trained on labelled data and relies on them to infer details about new information.

A new API to replace Java Native Interface (JNI) and enhancements in switch expressions and statements (preview) are among the features

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The JDK 17 is a long-term support (LTS) version, which means it has Oracle support for many years to come. Other LTS JDKs are Java 8 and Java 11. LTS JDKs are released every three years and non-LTS every six months.

In comparison, LTS versions’ support lasts for several years…

Vinicius Monteiro

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