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Serve Machine Learning Models via REST APIs in Under 10 Minutes

KDnuggets

Wrapping Up That’s it — and it’s already better than most demos. In this article, you will learn how we’ll go from a simple machine learning model to a production-ready API using FastAPI, one of Python’s fastest and most developer-friendly web frameworks, in just under 10 minutes. What we’ve built is more than just a toy example.

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Deploying the Magistral vLLM Server on Modal

KDnuggets

delta.content if content: print(content, end="", flush=True) print("n[END OF STREAM]") except Exception as e: print(f"[ERROR] Streaming demo failed: {e}") print("n" + "=" * 40 + "n") # 3. to test various vLLM server functionalities, including simple chat completions and streaming responses.

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Generative AI: A Self-Study Roadmap

KDnuggets

Prompt Engineering Excellence Prompt engineering transforms generative AI from impressive demo to practical tool. Well-designed prompts consistently produce useful outputs, while poor prompts lead to inconsistent, irrelevant, or potentially harmful results.

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Large Language Models: A Self-Study Roadmap

Flipboard

Step 1: Cover the Fundamentals You can skip this step if you already know the basics of programming, machine learning, and natural language processing. Step 2: Understand Core Architectures Behind Large Language Models Large language models rely on various architectures, with transformers being the most prominent foundation.

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5 Fun Generative AI Projects for Absolute Beginners

Flipboard

. # Wrapping Up Each of these projects teaches you something essential: Text → Image → Voice → Fine-tuning → Retrieval If youre just getting into Gen AI and want to actually build stuff, not just play with demos, this is your blueprint. Start from the one that excites you most. And remember, its okay to break things. That’s how you learn.

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Building intelligent AI voice agents with Pipecat and Amazon Bedrock – Part 2

AWS Machine Learning Blog

While the cascaded models approach outlined in Part 1 is flexible and modular, it requires orchestration of automatic speech recognition (ASR), natural language processing (NLU), and text-to-speech (TTS) models. Amazon Nova Sonic and Pipecat in action The demo showcases a scenario for an intelligent healthcare assistant.

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Using natural language in Amazon Q Business: From searching and creating ServiceNow incidents and knowledge articles to generating insights

AWS Machine Learning Blog

Enter the following information for your Amazon Q Business application: Application name : Enter a name for quick identification, such as my-demo-application. By using natural language processing capabilities, enterprises can streamline operations, enhance user productivity, and deliver better customer experiences.

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