How can I effectively scale my data science models?
Scaling data science models involves optimizing performance and managing resources. Are you looking for techniques or tools?
I'm interested in techniques. What are some best practices?
Some best practices include using distributed computing, optimizing algorithms, and leveraging cloud services for scalability.
Can you explain how distributed computing works in this context?
Sure! Distributed computing allows you to split tasks across multiple machines, which can process data in parallel, speeding up model training.
What tools can help with distributed computing?
Popular tools include Apache Spark, Dask, and TensorFlow, which support distributed training and data processing.
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