Remove 12 github-alternatives-for-data-science-projects
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How to Version Control Data in ML for Various Data Sources

The MLOps Blog

Data versioning control is an important concept in machine learning, as it allows for the tracking and management of changes to data over time. As data is the foundation of any machine learning project, it is essential to have a system in place for tracking and managing changes to data over time.

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Unlocking efficiency: Harnessing the power of Selective Execution in Amazon SageMaker Pipelines

AWS Machine Learning Blog

It simplifies the development and maintenance of ML models by providing a centralized platform to orchestrate tasks such as data preparation, model training, tuning and validation. The sample code for a full end-to-end walkthrough is available in the GitHub repo. The following diagram illustrates the pipeline behavior with a full run.

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Evaluation Derangement Syndrome (EDS) in the GPU-poor’s GenAI. Part 1: the case for Evaluation-Driven Development

deepsense.ai

analyze its intricate relationship with GPU inequality [4] and address how the ‘GPU-rich’ (a handful of firms with thousands of the strongest GPUs, as well as resources like data, engineers, and labelers) approach the problem of GenAI evaluation, in contrast to the harsh realities of the ‘GPU-poor’ (everyone else, really).

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Beyond OpenAI in Commercial LLM Landscape

John Snow Labs

This blog post explores the emerging players in the commercial large language model (LLM) landscape, namely Anthropic, Cohere, Mosaic ML, Cerebras, Aleph Alpha, AI21 Labs and John Snow Labs. In this blog post, we will dive into the fascinating ecosystem of LLM companies. billion in funding by June 2023. Known for their GPT-3.5

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