Data Journey with Yetunde Dada & Ivan Danov (QuantumBlack) - Kedro (an open-source MLOps framework) - introduction, benefits, use-cases, data & insights used for its development
Yetunde Data and Ivan Danov both live in London, work at QuantumBlack, and develop Kedro which is an open-source MLOps project. Yetunde works as a Director of Product Management, while Ivan works as a Senior Principal Machine Learning Engineer and the Engineering Director of Kedro.
QuantumBlack, a McKinsey company is a data science and advanced analytics company that works with customers from various industries. QuantumBlack was founded in 2009 and has its headquarters in London, United Kingdom. The company became a part of McKinsey & Company, a global management consulting firm, in 2015, and now operates as part of McKinsey's global analytics practice.
Topics that we talk about:
What Kedro is and what problems it solves
Reasons why different groups of data practitioners useKedro
Differences between companies that use and don't use Kedro
Companies that use Kedro in production e.g. Telksomsel (Indonesia's largest telecom) - blog post
Data and statistics that describe the adoption of Kedro
When to use Kedro vs. Jupyter Notebooks
Running Kedro everywhere, on all clouds and on-premise using various Kedro plugins e.g. VertexAI, Azure ML, SageMaker - blog post
Using data, analytics, and community-driven insights in the product development of Kedro e.g. Kedro-Telemetry, Github, online training
Current challenges, milestones, and focus areas for Kedro e.g. simpler configuration
Trends in the MLOpslandscape e.g. so many MLOps tools, LLMOPs
Integration between Iguazio & QuantumBlack, and its plans for Kedro
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