Remove 2017 Remove ML Remove Natural Language Processing
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Navigating tomorrow: Role of AI and ML in information technology

Dataconomy

With the ability to analyze a vast amount of data in real-time, identify patterns, and detect anomalies, AI/ML-powered tools are enhancing the operational efficiency of businesses in the IT sector. Why does AI/ML deserve to be the future of the modern world? Let’s understand the crucial role of AI/ML in the tech industry.

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NLP-Powered Data Extraction for SLRs and Meta-Analyses

Towards AI

Natural Language Processing Getting desirable data out of published reports and clinical trials and into systematic literature reviews (SLRs) — a process known as data extraction — is just one of a series of incredibly time-consuming, repetitive, and potentially error-prone steps involved in creating SLRs and meta-analyses.

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Getting Started with AI

Towards AI

As a reminder, I highly recommend that you refer to more than one resource (other than documentation) when learning ML, preferably a textbook geared toward your learning level (beginner/intermediate / advanced). In ML, there are a variety of algorithms that can help solve problems. Packt, ISBN: 978–1787125933, 2017.

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Deploy large language models for a healthtech use case on Amazon SageMaker

AWS Machine Learning Blog

To support overarching pharmacovigilance activities, our pharmaceutical customers want to use the power of machine learning (ML) to automate the adverse event detection from various data sources, such as social media feeds, phone calls, emails, and handwritten notes, and trigger appropriate actions.

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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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AI’s Got Some Explaining to Do

Towards AI

It’s particularly useful in natural language processing [3]. These massive models, from OpenAI and others, can process and generate human-like text, but understanding their decision-making process is far from straightforward [7]. For more articles on AI in business, feel free to explore my Medium profile.

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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. The images document the land cover, or physical surface features, of ten European countries between June 2017 and May 2018. The following are a few example RGB images and their labels.

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