review

As I prepare for my final Machine Learning interview with Lyft, I look back on my Data Science career and projects. I also want to give a brief overview of the subjects that are useful for machine learning and data science. Data science type positions: 1. Basic statistics 2. Basic probability 3. Linear Regression 4. Normal equation It is difficult to draw the line precisely between machine learning and data science. [Read More]

Paper review: (What’s in a Name? Reducing Bias in Bios Without Access to Protected Attributes)[https://arxiv.org/abs/1904.05233] Overall, I have a negative opinion of this paper. It introduces a novel way of bias mitigation, but provides little theoretical justification for why such an approach is useful, and also does not compare their work with any previous work. More over, I am extremely skeptical of the entire point of their paper, which is that we do not have access to protected attributes and so should find a way of providing fairness without looking at protected attributes. [Read More]