ODSC West 2018 Review: Have You Been to Machine Learning Mecca?
With ODSC West 2018 in the history logs, it didn’t disappoint. Conferences can be overblown, and usually in proportion to the number of buzzwords marketed in its runup. ODSC West wasn’t; I went home with a number of practical tricks I will apply to the machine learning problems that... Read more
Crash Course: Pool-Based Sampling in Active Learning
Active learning is a class of machine learning problems where labeled data isn’t available for supervised algorithms. Let’s take the classic setup as an example. Say we have pictures of birds and want to classify them by type, but the images don’t have labels for what kind of bird... Read more
Classic Regularization Techniques in Neural Networks
Neural networks are notoriously tricky to optimize. There isn’t a way to compute a global optimum for weight parameters, so we’re left fishing around in the dark for acceptable solutions while trying to ensure we don’t overfit the data. This is a quick overview of the most popular approaches... Read more
Three Ways Researchers are Using Data Science for Good
Data experts have long identified marginalization and narrow-minded problem solving as some of the biggest challenges facing data science. When large technology enterprises only seek solutions to problems they face within their company and their communities, it exacerbates inequalities. But companies, nonprofits, and individuals across the globe are making... Read more
9 Reasons Why You Should Go To a Career Fair
Tech companies have been known to ask… interesting…questions during interviews, such as the famous “How many golf balls can you fit in a school bus?” (It’s 660,000, apparently.) Whether it’s at Google, Facebook, Apple, or another company hiring for a data science position, you can bet that the interview(s) will be... Read more