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print(“\n📊 MODEL EVALUATION\n”) eval_results = trainer.evaluate() print(” Evaluation Results:”) for key, value in eval_results.items(): if isinstance(value, float): print(f” {key:<25}: {value:.4f}”) from sklearn.metrics import classification_report, confusion_matrix preds_output…

Pandas DataFrames provide powerful tools for selecting and indexing data efficiently. The two most commonly used indexers are .loc and .iloc. The .loc method selects data…

Image by Editor   # Introduction  Vertex AI Search, formerly known as Enterprise Search on Google Cloud, represents a significant evolution in how organizations can implement intelligent…

In production generative AI applications, we encounter a series of errors from time to time, and the most common ones are requests failing with 429 ThrottlingException…

Route planning on Amazfit watches isn’t just one thing. It includes GPX file imports, route creation in the Zepp Health app and, on some models, even…

AI and ML developers often work with local datasets while preprocessing data. Engineering features, and building prototypes make this easy without the overhead of a full…

Large language models are powerful, but on their own they have limitations. They cannot access live data, retain long-term context from previous conversations, or perform actions…

Along with the increasing sophistication of cyberattacks today, modern software applications have become increasingly complex and reliant on third-party components.Rarely are software applications built from scratch;…

The Rodecaster series of podcast mixers have become a mainstay among audio creatives. Last year, the company expanded the line with its first multimedia model —…

In this tutorial, we develop a comprehensive benchmarking framework to evaluate various types of agentic AI systems on real-world enterprise software tasks. We design a suite…