Blog
Data Science & ML
Computer Vision at Scale With Dask and PyTorch
This tutorial walks through how to use PyTorch and Dask to train an image recognition model across a GPU cluster.
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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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Random Forest on GPUs: 2000x Faster than Apache Spark
This blog post compares using RAPIDS and Dask vs Apache Spark for model training
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Supercharging Hyperparameter Tuning with Dask
The distributed computing framework Dask is great for hyperparameter tuning, since you can train different parameter sets concurrently.
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Practical Issues Setting up Kubernetes for Data Science on AWS
Data science has unique workflows that don't always match those of software engineers and require special setup for Kubernetes.
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Setting Up Your Data Science & Machine Learning Capability in Python
Python is a great language to base your DS/ML framework on, and allows you to avoid being locked into one vendor specific framework.
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