Remove BERT Remove Data Analysis Remove Data Extraction
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10 Best Prompt Engineering Courses

Unite.AI

The second course, “ChatGPT Advanced Data Analysis,” focuses on automating tasks using ChatGPT's code interpreter. teaches students to automate document handling and data extraction, among other skills. This 10-hour course, also highly rated at 4.8,

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Introduction to Large Language Models (LLMs): An Overview of BERT, GPT, and Other Popular Models

John Snow Labs

They can process and analyze large volumes of text data efficiently, enabling scalable solutions for text-related challenges in industries such as customer support, content generation, and data analysis. BERT excels in understanding context and generating contextually relevant representations for a given text.

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Digging Into Various Deep Learning Models

Pickl AI

The convolution layer applies filters (kernels) over input data, extracting essential features such as edges, textures, or shapes. Pooling layers simplify data by down-sampling feature maps, ensuring the network focuses on the most prominent patterns.

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Accurate Extracting of Cancer Biomarkers from Free-Text Clinical Notes

John Snow Labs

Research And Discovery: Analyzing biomarker data extracted from large volumes of clinical notes can uncover new correlations and insights, potentially leading to the identification of novel biomarkers or combinations with diagnostic or prognostic value. This information is crucial for data analysis and biomarker research.

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Large Language Models in Pathology Diagnosis

John Snow Labs

The potential of LLMs, in the field of pathology goes beyond automating data analysis. These early efforts were restricted by scant data pools and a nascent comprehension of pathological lexicons. This capability opens up possibilities in pathology where accurate and timely diagnoses can greatly influence patient outcomes.