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From Rulesets to Transformers: A Journey Through the Evolution of SOTA in NLP

Mlearning.ai

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. Evolution of NLP Models To understand the full impact of the above evolutionary process.

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Named Entity Recognition With SpaCy

Heartbeat

Named entity recognition (NER) is a subtask of natural language processing (NLP) that involves automatically identifying and classifying named entities mentioned in a text. Pre-processing: The text is first pre-processed by removing any unnecessary information, such as stop words, and tokenizing the text into individual words.

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Machine Learning vs. Deep Learning - A Comparison

Heartbeat

Deep learning is utilized in many fields, such as robotics, speech recognition, computer vision, and natural language processing. In many of these domains, it has cutting-edge performance and has made substantial advancements in areas like autonomous driving, speech and picture recognition, and language translation.

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The Age of Health Informatics: Part 1

Heartbeat

By analyzing historical data and utilizing predictive machine learning algorithms like BERT, ARIMA, Markov Chain Analysis, Principal Component Analysis, and Support Vector Machine, they can assess the likelihood of adverse events, such as hospital readmissions, and stratify patients based on risk profiles.

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Where AI is headed in the next 5 years?

Pickl AI

Machine Learning and Neural Networks (1990s-2000s): Machine Learning (ML) became a focal point, enabling systems to learn from data and improve performance without explicit programming. Techniques such as decision trees, support vector machines, and neural networks gained popularity.

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What are Large Language Models (LLMs)?

phData

What Are Large Language Models? Large Language Models are deep learning models that recognize, comprehend, and generate text, performing various other natural language processing (NLP) tasks. Translation: LLMs excel at translating text between different languages, improving global communication.

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Exploring the dynamic fusion of AI and the IoT

Dataconomy

This enables them to respond quickly to changing conditions or events. Supervised learning algorithms, like decision trees, support vector machines, or neural networks, enable IoT devices to learn from historical data and make accurate predictions.