Comet LLM is an observability platform and evaluation framework designed for large language model applications and agentic workflows. It functions as a system for tracing, monitoring, and debugging execution flows while providing tools for prompt optimization and the enforcement of AI safety guardrails. The platform distinguishes itself through a combination of model-based scoring and heuristic metrics to quantify output quality and detect hallucinations. It includes a dedicated prompt and agent optimizer with an interactive playground for refining templates and tool configurations. For retri
The Data Science Lifecycle Process is a process for taking data science teams from Idea to Value repeatedly and sustainably. The process is documented in this repo.
Examples of Machine Learning code using Comet.ml
Template repository for data science lifecycle project
Feature engineering and machine learning: together at last!
Les fonctionnalités principales de asavinov/lambdo sont : MLOps and Pipelines, Data Science Tooling, Data Science Tools.
Les alternatives open-source à asavinov/lambdo incluent : dslp/dslp — The Data Science Lifecycle Process is a process for taking data science teams from Idea to Value repeatedly and… iterative/cml — CML is a pipeline automation tool for training and evaluating machine learning models, functioning as a CI/CD system… comet-ml/comet-examples — Examples of Machine Learning code using Comet.ml. comet-ml/comet-llm — Comet LLM is an observability platform and evaluation framework designed for large language model applications and… dslp/dslp-repo-template — Template repository for data science lifecycle project. iterative/dvc — DVC is a data versioning tool and pipeline orchestrator designed to track large datasets and machine learning models.…