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Is There Bias in Your AI Model? Do You Know How It Got There?
Bias comes in a variety of forms, all of them potentially damaging to the efficacy of your ML algorithm. Our Chief Data Scientist specializes in training data bias, the source of most headlines about AI failures. Our overview – Four Types of AI Bias – is a guide for detecting and mitigating bias.
In the News
AI is sending people to jail—and getting it wrong
Using historical data to train risk assessment tools could mean that machines are copying the mistakes of the past.
Three charts show how China’s AI industry is propped up by three companies
More than half of the country’s major AI players have funding ties that lead back to Baidu, Alibaba, and Tencent.
Workplace
Demand and salaries for Data Scientists continue to climb
Data-science job openings are expanding faster than the number of technologists looking for them
Airbnb Data Science Interview Questions
Learning
Few-shot learning
Thoughts on progress made and challenges ahead in few-shot learning (i.e. learning from tiny datasets). Slides by Hugo Larochelle (Google Brain)
What can neural networks learn?
"Neural networks are famously difficult to interpret. It’s hard to know what they are actually learning when we train them. Let’s take a closer look and see whether we can build a good picture of what’s going on inside."
Looking Back at Google’s AI Research Efforts in 2018
Software tools & code
Machine Learning for Kids
Web-based list of ML projects aimed at children aged 8 to 16. They cover simple computer vision, NLP, game mechanics, and are available on "scratch", a coding platform for children.
Uber Manifold
Model-Agnostic Visual Debugging Tool for Machine Learning
What’s coming in TensorFlow 2.0
Some thoughts
How AI will turn us all into Filmmakers
About
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