Use the vitals package with ellmer to evaluate and compare the accuracy of LLMs, including writing evals to test local models.
From deep research to image generation, better prompts unlock better outcomes. Here's the step-by-step formula.
Kennesaw State University (KSU) is stepping into the future of workforce-ready education with the launch of a new Bachelor’s degree ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...
Abstract: To tackle the challenge of data diversity in sentiment analysis and improve the accuracy and generalization ability of sentiment analysis, this study first cleans, denoises, and standardizes ...
The use of modern technologies, including Immersive Mixed Reality (IMR) technologies, to present information on climate change has become essential due to their ability to simplify information and ...
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM ...
This paper focuses on the nonlinear correlation between investor sentiment and stock returns and conducts in-depth research with the aid of deep learning and text mining techniques. First of all, sort ...
Traditional bibliometric approaches to research impact assessment have predominantly relied on citation counts, overlooking the qualitative dimensions of how research is received and discussed.
In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...
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