In my journey with Spring, I’ve discovered the power of combining AI with testing frameworks. Here’s a brief dive into AI Evaluators. 🌟
AI Evaluators help in assessing the performance of Machine Learning models by providing reliable evaluation metrics. When integrated with Spring, it allows for more dynamic and intelligent testing patterns.
Key highlights:
- Enhanced Testing: Leverage AI to automate the testing process. - Custom Metrics: Set up tailored evaluation metrics for specific use cases. - Integration: Seamlessly blend with existing Spring applications.
Here's a simple example of setting up an AI evaluator:
AIModelEvaluator evaluator = new AIModelEvaluator(); evaluator.addMetric(new AccuracyMetric()); evaluator.evaluate(model, testData);
Incorporating AI evaluators not only improves accuracy but also accelerates the testing process. As we embrace AI, let’s leverage it for smarter software engineering! 💡
Feel free to share your thoughts or experiences with AI in testing!
In my journey with Spring, I’ve discovered the power of combining AI with testing frameworks. Here’s a brief dive into AI Evaluators. 🌟
AI Evaluators help in assessing the performance of Machine Learning models by providing reliable evaluation metrics. When integrated with Spring, it allows for more dynamic and intelligent testing patterns.
Key highlights:
- Enhanced Testing: Leverage AI to automate the testing process. - Custom Metrics: Set up tailored evaluation metrics for specific use cases. - Integration: Seamlessly blend with existing Spring applications.
Here's a simple example of setting up an AI evaluator:
AIModelEvaluator evaluator = new AIModelEvaluator(); evaluator.addMetric(new AccuracyMetric()); evaluator.evaluate(model, testData);
Incorporating AI evaluators not only improves accuracy but also accelerates the testing process. As we embrace AI, let’s leverage it for smarter software engineering! 💡
Feel free to share your thoughts or experiences with AI in testing!
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The lead from Wall Street offers little clarity as the major averages opened lower on Friday and then bounced back and forth across the unchanged line, finally finishing mixed and little changed.The Dow added 33.18 points or 0.10 percent to finish at 34,798.00, while the NASDAQ eased 4.54 points or 0.03 percent to close at 15,047.70 and the S&P 500 rose 6.50 points or 0.15 percent to end at 4,455.48. For the week, the Dow rose 0.6 percent, the NASDAQ added 0.1 percent and the S&P gained 0.5 percent.The lackluster performance on Wall Street came on uncertainty about the outlook for the markets following recent volatility.
The STAR Market, as is implied by the name, is heavily geared toward smaller innovative tech companies, in particular those engaged in strategically important fields, such as biopharmaceuticals, 5G technology, semiconductors, and new energy. The STAR Market currently has 340 listed securities. The STAR Market is seen as important for China’s high-tech and emerging industries, providing a space for smaller companies to raise capital in China. This is especially significant for technology companies that may be viewed with suspicion on overseas stock exchanges.
