Issue-number: 284

summary: Leveling-up w/ SQL. Making sense of COVID-19 models. Deploying ML data. Setting up a laptop for DS work. Tornado plots. ML in moderation. number: 284 title: Issue 284 url: https://dataelixir.com/issues/284 published_at06.05.20, 16:37

Issue-number: 279

summary: Technical freelancing. Julia review. Jupyter visual debugger. Stanford CS472: Data Science for COVID-19. Privacy & pandemics. ggplot2 workshop. number: 279 title: Issue 279 url: https://dataelixir.com/issues/279 published_at31.03.20, 23:58

Issue-number: 281

summary: A Life in Games. On-campus w/ COVID-19. Grammar of Tables. Monitoring ML. Peer Reviews for DS. Oceans of data. number: 281 title: Issue 281 url: https://dataelixir.com/issues/281 published_at15.04.20, 00:28

Issue-number: 283

summary: Recommender Systems. What you should know about DBs. Automatic code cleaning. Stanford CS229: ML. Game Boy emulator. Uncertainty viz. 3D maps. number: 283 title: Issue 283 url: https://dataelixir.com/issues/283 published_at28.04.20, 23:23

Issue-number: 280

summary: ⚽ Analytics Handbook. Product mgmt for AI. Forecasting Best Practices. Bayesian Data Analysis. scikit-learn tips. ML dev platforms. number: 280 title: Issue 280 url: https://dataelixir.com/issues/280 published_at07.04.20, 20:25

Issue-number: 285

summary: Feature Stores. Black box optimization. Measuring fairness. Streaks w/ Python. Prediction is hard. Keeping track of the apps that track you. number: 285 title: Issue 285 url: https://dataelixir.com/issues/285 published_at12.05.20, 22:13

Issue-number: 282

summary: Forecasting s-curves. Linear Algebra Done Right. Backpropagation 101. Estimating Rt. Upset plots. Visualizing uncertainty. ML Interpretability. number: 282 title: Issue 282 url: https://dataelixir.com/issues/282 published_at21.04.20, 21:25

Issue-number: 286

summary: 25 hot new tools. Advanced SQL. Supervised ML case studies. Practical A/B testing. Scrollytelling tutorial. AI in healthcare. number: 286 title: Issue 286 url: https://dataelixir.com/issues/286 published_at19.05.20, 23:39

Issue-number: 287

summary: 📊+❤️. ML Best Practices. Evaluating metrics. Differential privacy. Monitoring Data Quality at Scale. Learning data viz. number: 287 title: Issue 287 url: https://dataelixir.com/issues/287 published_at27.05.20, 04:34

Issue-number: 288

summary: Practical Python. Ultimate guide to ML deployment. Visualizing reality. Advanced Statistical Computing w/ R. How-to create interactive tutorials. number: 288 title: Issue 288 url: https://dataelixir.com/issues/288 published_at03.06.20, 04:24