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An open-source framework for data science codePricing:
- Open Source
Kedro is an ML development framework for creating reproducible, maintainable, modular data science code. Kedro improves AI project development experience via data abstraction and code organization. Using lightweight data connectors, it provides a centralized data catalog to manage and track datasets throughout a project. This enables data scientists to focus on building production level code through Kedro's data pipelines, enabling other stakeholders to use the same pipelines in different parts of the system.
#Data Science And Machine Learning #Data Pipelines #Python Web Framework 2 social mentions
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Application and Data, Data Stores, and Big Data ToolsPricing:
- Open Source
Delta Lake is a storage layer framework that provides reliability to data lakes. It addresses the challenges of managing large-scale data in lakehouse architectures, where data is stored in an open format and used for various purposes, like machine learning (ML). Data engineers can build real-time pipelines or ML applications using Delta Lake because it supports both batch and streaming data processing. It also brings ACID (atomicity, consistency, isolation, durability) transactions to data lakes, ensuring data integrity even with concurrent reads and writes from multiple pipelines.
#Development #Office & Productivity #Data Dashboard 35 social mentions
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Deepchecks is a QA platform that inspects the production data and models.Pricing:
- Open Source
Deepchecks is an ML monitoring tool for continuously testing and validating machine learning models and data from an AI project's experimentation to the deployment stage. It provides a wide range of built-in checks to validate model performance, data integrity, and data distribution. These checks help identify issues like model bias, data drift, concept drift, and leakage.
#AI #Machine Learning #QA 2 social mentions