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Data Science

Product Management for AI

By Ann Spencer

Data Science

MNIST Expanded: 50,000 New Samples Added

By Ann Spencer

Data Science

Machine Learning Product Management: Lessons Learned

By Ann Spencer

Data Science

Can Data Science Help Us Make Sense of the Mueller Report?

By Josh Poduska

Machine Learning

Machine Learning in Production: Software Architecture

By John Joo

Data Science

Comparing the functionality of open source NLP libraries

By Maziyar Panahi & David Talby

Perspective

On Collaboration Between Data Science, Product, and Engineering Teams

By Ann Spencer

Machine Learning

Machine Learning Projects: Challenges and Best Practices

By Lukas Biewald

Data Science

Model interpretability with TCAV (Testing with Concept Activation Vectors)

By Domino

Code

SHAP and LIME Python libraries: Part 2 - using SHAP and LIME

By Josh Poduska

Machine Learning

Creating Multi-language Pipelines with Apache Spark or Avoid Having to Rewrite spaCy into Java

By Holden Karau

Data Science

Data Science vs Engineering: Tension Points

By Ann Spencer

Code

SHAP and LIME Python Libraries: Part 1 - Great Explainers, with Pros and Cons to Both

By Josh Poduska

Data Science

Justified Algorithmic Forgiveness?

By Domino

Data Science

Trust in LIME: Yes, No, Maybe So? 

By Ann Spencer

Benchmark

Benchmarking NVIDIA CUDA 9 and Amazon EC2 P3 Instances Using Fashion MNIST

By Josh Poduska

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