Difference between revisions of "Bias and Variances"
m |
|||
| Line 17: | Line 17: | ||
* [http://developer.ibm.com/articles/machine-learning-and-bias/ Machine learning and bias | IBM] [http://aif360.mybluemix.net/?_ga=2.258555210.1353694320.1576870371-739966746.1575208440 AI Fairness 360 Open Source Toolkit] extensible open source toolkit can help you examine, report, and mitigate discrimination and bias in machine learning models throughout the AI application lifecycle. Containing over 70 fairness metrics and 10 state-of-the-art bias mitigation algorithms | * [http://developer.ibm.com/articles/machine-learning-and-bias/ Machine learning and bias | IBM] [http://aif360.mybluemix.net/?_ga=2.258555210.1353694320.1576870371-739966746.1575208440 AI Fairness 360 Open Source Toolkit] extensible open source toolkit can help you examine, report, and mitigate discrimination and bias in machine learning models throughout the AI application lifecycle. Containing over 70 fairness metrics and 10 state-of-the-art bias mitigation algorithms | ||
* [http://www.usatoday.com/story/tech/2020/07/22/uber-lyft-algorithms-discriminate-charge-more-non-white-areas/5481950002/ Was your Uber, Lyft fare high because of algorithm bias? | Coral Murphy - USA TODAY] | * [http://www.usatoday.com/story/tech/2020/07/22/uber-lyft-algorithms-discriminate-charge-more-non-white-areas/5481950002/ Was your Uber, Lyft fare high because of algorithm bias? | Coral Murphy - USA TODAY] | ||
| + | * [http://research.google.com/bigpicture/attacking-discrimination-in-ml/ Attacking discrimination with smarter machine learning |] [[Creatives#Martin Wattenberg |Martin Wattenberg]], [[Creatives#Fernanda Viegas |Fernanda Viegas]], and Moritz Hardt | ||
| + | |||
https://cdn-images-1.medium.com/max/800/1*RvLVTYBiRXogAr6Ap5jgLA.png | https://cdn-images-1.medium.com/max/800/1*RvLVTYBiRXogAr6Ap5jgLA.png | ||
Revision as of 08:07, 21 August 2020
Youtube search... ...Google search
- A Basic Recipe for Machine Learning | Hafidz Zulkifli
- Inductive Bias | Wikipedia
- Overfitting Challenge
- Evaluation Measures - Classification Performance
- This is how AI bias really happens—and why it’s so hard to fix | Karen Hao
- Top 6 most common statistical errors made by data scientists | Richa Bhatia - Analytics India
- Data Science Concepts Explained to a Five-year-old | Megan Dibble - Toward Data Science
- Machine learning and bias | IBM AI Fairness 360 Open Source Toolkit extensible open source toolkit can help you examine, report, and mitigate discrimination and bias in machine learning models throughout the AI application lifecycle. Containing over 70 fairness metrics and 10 state-of-the-art bias mitigation algorithms
- Was your Uber, Lyft fare high because of algorithm bias? | Coral Murphy - USA TODAY
- Attacking discrimination with smarter machine learning | Martin Wattenberg, Fernanda Viegas, and Moritz Hardt
