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In this video, I'll be telling you about NEO, a new AI agent that works inside VS Code and can act like an autonomous machine learning engineer, helping you build datasets, train models, deploy APIs, and create a UI from a single prompt.

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Key Takeaways:

🚀 NEO is an autonomous machine learning engineer built for AI, ML, and data workflows inside VS Code.
🧠 It plans tasks, generates synthetic datasets, trains models, and iterates based on results.
📁 The extension works locally with your project files, datasets, and workspace isolation for better privacy.
🔗 You can connect AWS S3, Hugging Face, Weights & Biases, GitHub, and Kaggle integrations.
🛠️ NEO can handle deployment by building inference APIs and even creating a frontend UI automatically.
📊 It provides detailed logs, recovery steps, and experiment tracking for more transparent workflows.
👍 Overall, NEO is a powerful AI teammate for practical machine learning development in VS Code.

AICodeKing

NEO is a VS Code extension that acts as an autonomous ML engineer, capable of building end-to-end AI pipelines from a single prompt. It handles data generation, model training, deployment, and UI creation without switching environments. A demo shows it building a chat moderation pipeline from scratch — generating synthetic data, training a classifier, creating a REST API, and building a frontend — all locally within VS Code. It supports integrations with AWS S3, HuggingFace, Weights & Biases, and Kaggle, stores credentials in an encrypted local vault, and offers self-correcting behavior when errors occur. It covers tabular ML, computer vision, LLM fine-tuning, and RAG workflows.

NEO: The AI Agent That Builds AI Models, Agents & Apps From One Prompt