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dslp/dslp-repo-template

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202 stars·60 forks·Python·12 views

Dslp Repo Template

Template repository for data science lifecycle project

Features

  • MLOps Articles - Template for structuring data science and machine learning projects.
  • MLOps and Pipelines - Template for structured data science projects.
  • Data Science Tooling - Standardized template for data science projects.
  • Data Science Tools - Standardized project structure for data science.

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Frequently asked questions

What does dslp/dslp-repo-template do?

Template repository for data science lifecycle project

What are the main features of dslp/dslp-repo-template?

The main features of dslp/dslp-repo-template are: MLOps Articles, MLOps and Pipelines, Data Science Tooling, Data Science Tools.

What are some open-source alternatives to dslp/dslp-repo-template?

Open-source alternatives to dslp/dslp-repo-template include: comet-ml/comet-llm — Comet LLM is an observability platform and evaluation framework designed for large language model applications and… iterative/cml — CML is a pipeline automation tool for training and evaluating machine learning models, functioning as a CI/CD system… asavinov/lambdo — Feature engineering and machine learning: together at last! comet-ml/comet-examples — Examples of Machine Learning code using Comet.ml. dslp/dslp — The Data Science Lifecycle Process is a process for taking data science teams from Idea to Value repeatedly and… iterative/dvc — DVC is a data versioning tool and pipeline orchestrator designed to track large datasets and machine learning models.…

Open-source alternatives to Dslp Repo Template

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  • comet-ml/comet-examplescomet-ml avatar

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  • comet-ml/comet-llmcomet-ml avatar

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    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

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  • asavinov/lambdoasavinov avatar

    asavinov/lambdo

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    Feature engineering and machine learning: together at last!

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  • dslp/dslpdslp avatar

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    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.

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