Machine Learning: A Quantitative Approach
Machine Learning: A Quantitative Approach [Liu, Henry H] on Amazon.com. *FREE* shipping on qualifying offers. Machine Learning: A Quantitative Approach…
Read more »Machine Learning Cohorts: A Synthesis
Contribute to dynamicwebpaige/kaggle-survey-spelunking development by creating an account on GitHub.
Read more »Scikit-Learn: Subtle Questions About Implementing Machine Learning Methods
Scikit-Learn: Subtle Questions About Implementing Machine Learning Methods with Examples…
Read more »Bag of Freebies for XR Hand Tracking: Machine Learning and OpenXR
Diving into the machine learning details that were implemented in our innovative, open source hand-tracking pipeline.
Read more »Machine Learning Can Reduce Worry About Nanoparticles in Food
Researchers at Texas A&M can predict whether metallic nanoparticles in soil are likely to be absorbed by plants, which could cause toxicity.
Read more »New Machine Learning Gems for Ruby
In August, I set out to improve the machine learning ecosystem for Ruby and wasn’t sure where it would go. Over the next 5 months, I ended up…
Read more »Thoughts on NLP’s Rapid Growth as a Super Popular Domain in Machine Learning
Thoughts on NLP’s Rapid Growth as a super popular domain in Machine Learning…
Read more »Benchmark: Using Machine Learning to Optimize Amazon RDS PostgreSQL Performance
Automatically optimize database configuration files using machine learning to improve performance and reduce costs.
Read more »Introducing MLOps.toys – Machine Learning & DevOps related projects
Meet MLOps Toys! A curated list of the machine learning tools & projects to support your ML infrastructure and ML platform.
Read more »Markpainting: Adversarial Machine Learning Meets Inpainting
Inpainting is a learned interpolation technique that is based on generative modeling and used to populate masked or missing pieces in an image; it has wide applications in picture editing and retouching. Recently, inpainting started being used for waterma…
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