Remove Books Remove Natural Language Processing Remove Supervised Learning
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The Rise of ChatGPT: A New Era of Artificial Intelligence

Becoming Human

Empowering Startups and Entrepreneurs | InvestBegin.com | investbegin The success of ChatGPT can be attributed to several key factors, including advancements in machine learning, natural language processing, and big data. NLP is a field of AI that focuses on enabling computers to understand and process human language.

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Gamification in AI?—?How Learning is Just a Game

Applied Data Science

. ⁍ Preface In 1986, Marvin Minsky , a pioneering computer scientist who greatly influenced the dawn of AI research, wrote a book that was to remain an obscure account of his theory of intelligence for decades to come. Language as a game: the field of Emergent Communication Firstly, what is language?

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Fundamentals of Data Mining

Data Science 101

Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD). The former is a term used for models where the data has been labeled, whereas, unsupervised learning, on the other hand, refers to unlabeled data. Classification. Regression.

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The Ascent of ChatGPT

ODSC - Open Data Science

Trained with 570 GB of data from books and all the written text on the internet, ChatGPT is an impressive example of the training that goes into the creation of conversational AI. ChatGPT is a next-generation language model (referred to as GPT-3.5) They can be used to generate news articles, stories, poems, and even code.

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How foundation models and data stores unlock the business potential of generative AI

IBM Journey to AI blog

Foundation models can be trained to perform tasks such as data classification, the identification of objects within images (computer vision) and natural language processing (NLP) (understanding and generating text) with a high degree of accuracy.

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10 Essential Topics to Master LLMs and Generative AI

ODSC - Open Data Science

Question-Answering Question-answering (QA) LLMs are a type of large language model that has been trained specifically to answer questions. They are trained on massive datasets of text and code, including text from books, articles, and code repositories. One common approach is to use supervised learning.

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Train self-supervised vision transformers on overhead imagery with Amazon SageMaker

AWS Machine Learning Blog

Training machine learning (ML) models to interpret this data, however, is bottlenecked by costly and time-consuming human annotation efforts. One way to overcome this challenge is through self-supervised learning (SSL). His specialty is Natural Language Processing (NLP) and is passionate about deep learning.

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