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2025-11-26 05:44:29 - Translate

How Artificial Intelligence Can Help Achieve a Clean Energy Future?
Introduction Nowadays, the world is using more energy than ever before and climate change is getting worse than ever. If you are looking to protect your planet, then this may need a cleaner and smarter way of producing as well as using the energy. There are many renewable sources such as solar and wind are growing fast, but they also bring some challenges with them. Because they will not...

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2025-11-15 09:59:06 - Translate

The Rise of Agentic AI: How Autonomous Agents Are Transforming Industries
Technology has changed a lot over the years, but Agentic AI is something new. It is not just regular automation. Agentic AI means machines can do things by themselves, make small choices, and learn from what happens around them. These systems do not just follow fixed steps like old machines. They can plan, reason, and sometimes even improve the way they work. This has made businesses look at...

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2025-10-30 05:04:39 - Translate

How Python Works With Databases Without Extra Tools?
Introduction Python has become the go-to language for everything from data analysis to automation. But one thing that often surprises beginners is this - Python doesn’t always need heavy external libraries or ORM frameworks to connect to a database. It can talk directly to databases using built-in modules and native drivers. In fact, this built-in connection style gives developers a...

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2025-10-09 10:03:57 - Translate

Understanding the Software Testing Lifecycle
Software testing refers to an essential phase in the software development life cycle (SDLC) that helps in evaluating the reliability, functionality, as well as avoiding defects in applications. It entails a process whereby software runners are methodically fixed to detect defects, approve features, and ensure performance is met, deliverable and feasible results to the business and user. Through...

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2025-09-27 04:42:16 - Translate

What is Model Deployment in Machine Learning?
Introduction Model deployment is the step where a trained machine learning model is used in real life. This means the model starts giving predictions for real data. You can see it in apps and websites you use every day. Model deployment is important because it makes the machine learning project useful and not just a study project. If you want to learn how to deploy models easily you can join a...

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2025-09-27 04:34:32 - Translate

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