To train an ML model, you need to be proficient in algorithms, write code, endlessly tune hyperparameters which is a high entry barrier for most people.

An open-source project Plexe significantly lowers this threshold: You describe the task in plain language and it automatically assembles machine learning for it.

🟢 How it works?

☞ Explain in a human-friendly way what you want to predict, what the input data is and what the output should be.

⁠☞ Next the system, through a combination of several agents, goes through the entire pipeline: data analysis, solution plan, code generation, tests, and quality assessment.

⁠☞ Supports various LLM providers: OpenAI, Anthropic, Ollama, and others. Plus, it can automatically derive the data structure or even generate a synthetic dataset.

⁠☞ There's also distributed training on Ray inside: you can run multiple model variants in parallel and significantly speed up the process.

GitHub

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