Eugene Yan • 1/19/2022

How to Keep Learning about Machine Learning

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The article offers actionable advice for continuous learning in machine learning, emphasizing hands-on experimentation with new tools (like Spark, PyTorch), undertaking personal projects, and engaging with the community through conferences and sharing knowledge. It addresses the challenge of keeping pace with rapid advancements in algorithms and frameworks.

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#Machine Learning #data processing #Spark
How to Keep Learning about Machine Learning

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