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    Web of circles and squares illustrating a data lineage process

    What Is Data Lineage?

    Data lineage refers to the full history of data points and actions taken on them throughout a machine learning (ML) workflow. By inspecting a...
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    Understanding Performance Bias With the Valor Model Evaluation Service

    Machine learning benchmarks like ImageNet, COCO, and LLM Leaderboard usually target a single metric, such as accuracy for classification tasks or...
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    To Build or Buy an MLOps Platform?

    It’s the oldest debate in business (or at least the oldest since Silicon Valley invented software-as-a-service). “If we need software, should we buy...
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    A graphic showing multiple text boxes and a magnifying lens to indicate text classification.

    Text Classification With LLMs: A Roundup of the Best Methods

    This blog post is part of a series on using large language models for text classification. View the other posts here: LLMs for Text Classification:...
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    Unsupervised text classification

    Unsupervised Text Classification: Categorize Natural Language Data With LLMs

    This blog post is part of a series on using large language models for text classification. View the other posts here:
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    Text classification using the Llama model

    LLMs for Text Classification: A Guide to Supervised Learning

    By Benjamin Nativi, Will Porteous, and Linnea Wolniewicz Large language models (LLMs) like GPT, which powers Open AI’s ChatGPT, have sparked a...
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    Striveworks secures patent for innovative data lineage process

    Striveworks Secures Patent for Innovative Data Lineage Process

    The new process grants greater transparency into machine learning workflows and allows for better data governance. Originally published on January 4,...
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    Overhead photography of cars in a parking lot; a yellow car has been selected for computer vision.

    Demystifying CV: The Power of Convolution in Neural Networks

    Computer vision is an innovative field of research that aims to provide computers with an understanding of digital imagery, often through artificial...
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    Understanding Neural Networks and the Training Process

    Training a neural network involves a lot of mathematics, including linear algebra and multivariate calculus, and a lot of computation. The purpose of...
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    Two classifiers being combined into a single classifier. In general, the decision boundaries of the two classifiers cannot merely be superimposed; instead new boundaries must be learned that respect both tasks.

    Sequential Learning through Knowledge Distillation

    In the last blog post, we saw that neural networks can be simplified (or pruned) to alleviate their complexity and cost for computation. Often small...
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    Pruning ResNets for Fun and Profit

    What are Neural Networks? Neural networks are highly parameterized functions which can be trained to fit/represent/model data. Parameterized models...
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