Dataconomy

MARCH 17, 2025

Logistic regression Logistic regression is designed for binary classification tasks, predicting the likelihood of an event occurring based on input variables. It enhances data classification by increasing the complexity of input data, helping organizations make informed decisions based on probabilities.

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IBM Journey to AI blog

DECEMBER 20, 2023

And retailers frequently leverage data from chatbots and virtual assistants, in concert with ML and natural language processing (NLP) technology, to automate users’ shopping experiences. Classification algorithms include logistic regression, k-nearest neighbors and support vector machines (SVMs), among others.

Machine Learning 92

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Towards AI

MAY 3, 2023

In the realm of data science, seasoned professionals often carry out research to comprehend how similar issues have been tackled in the past. They investigate the most suitable algorithms, identify the best weights and hyperparameters, and might even collaborate with fellow data scientists in the community to develop an effective strategy.

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IBM Journey to AI blog

AUGUST 1, 2023

A foundation model is built on a neural network model architecture to process information much like the human brain does. Instead of spending time and effort on training a model from scratch, data scientists can use pretrained foundation models as starting points to create or customize generative AI models for a specific use case.

AI 70

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Pickl AI

SEPTEMBER 3, 2024

Here are some core responsibilities and applications of ANNs: Pattern Recognition ANNs excel in recognising patterns within data , making them ideal for tasks such as image recognition, speech recognition, and natural language processing.

Natural Language Processing 52

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AWS Machine Learning Blog

DECEMBER 5, 2023

Customers can create the custom metadata using Amazon Comprehend , a natural-language processing (NLP) service managed by AWS to extract insights about the content of documents, and ingest it into Amazon Kendra along with their data into the index. For example, metadata can be used for filtering and searching.

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