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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

Core features of end-to-end MLOps platforms End-to-end MLOps platforms combine a wide range of essential capabilities and tools, which should include: Data management and preprocessing : Provide capabilities for data ingestion, storage, and preprocessing, allowing you to efficiently manage and prepare data for training and evaluation.

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LLMOps: What It Is, Why It Matters, and How to Implement It

The MLOps Blog

LLMOps (Large Language Model Operations) focuses on operationalizing the entire lifecycle of large language models (LLMs), from data and prompt management to model training, fine-tuning, evaluation, deployment, monitoring, and maintenance. LLMOps is key to turning LLMs into scalable, production-ready AI tools.