Cross-Entropy Loss Function
When working on a Machine Learning or a Deep Learning Problem, loss/cost functions are used to optimize the model during training. The …
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This tutorial walks through how to use PyTorch and Dask to train an image recognition model across a GPU cluster.
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When working on a Machine Learning or a Deep Learning Problem, loss/cost functions are used to optimize the model during training. The …

This blog post compares using RAPIDS and Dask vs Apache Spark for model training

The distributed computing framework Dask is great for hyperparameter tuning, since you can train different parameter sets concurrently.

Data science has unique workflows that don't always match those of software engineers and require special setup for Kubernetes.

Python is a great language to base your DS/ML framework on, and allows you to avoid being locked into one vendor specific framework.

This article covers efficient ways to load data from Snowflake into a Dask distributed cluster.