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How Insurance Companies Use Data To Measure Risk And Choose Rates

Smart Data Collective

Insurance companies have access to stats on what make and model of car is stolen more often or involved in more crashes. For instance, the 2000 Honda Civic is the most stolen car in America and the Mitsubishi Mirage (in the 2013-2017 model range) has the most fatal crashes. Telematics. Safety Features.

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The AIgent: Using Google’s BERT Language Model to Connect Writers & Representation

Insight

In 2013, Robert Galbraith?—?an The AIgent was built with BERT, Google’s state-of-the-art language model. In this article, I will discuss the construction of the AIgent, from data collection to model assembly. Data Collection The AIgent leverages book synopses and book metadata. an aspiring author?—?finished

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Critical Components of Big Data Architecture for a Translation Company

Smart Data Collective

You might use predictive analysis-based data that can help you analyse buying trends or look at how the business might perform in a range of new markets. Sometimes big data models can look at which keywords and topics are trending on social media and, as translation company Tomedes points out, that can involve multiple languages.

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Benchmarking Performance: Your Options, Dos, Don'ts and To-Die-Fors!

Occam's Razor

See step four in the process for creating your Digital Marketing and Measurement Model.]. This recommendation also valuable for companies that have very unique business models, or face other unusual circumstances (geographic, size, amount of innovation, and many others). So how can you use your own data? See Page 269. :).

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Preprocess and fine-tune LLMs quickly and cost-effectively using Amazon EMR Serverless and Amazon SageMaker

AWS Big Data

Large language models (LLMs) are becoming increasing popular, with new use cases constantly being explored. This is where model fine-tuning can help. Before you can fine-tune a model, you need to find a task-specific dataset. Next, we use Amazon SageMaker JumpStart to fine-tune the Llama 2 model with the preprocessed dataset.

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Responses to Negative Data: Four Senior Leadership Archetypes.

Occam's Razor

Their most common reaction to negative data, if it makes it through, is to try to discredit it by asking analytically-nonsensical questions: What are the p-values of your multi-channel attribution model applied to performance of my strategy? They attack the data. You know my Care-Do-Impact model for analysis and storytelling.

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Why We Started the Data Intelligence Project

Alation

Two data-driven careers. In 2013 I joined American Family Insurance as a metadata analyst. Companies competing for data talent must demonstrate a commitment to building a modern data stack and to supporting a strong internal community of data professionals to attract top prospects.