Data Elixir Newsletter Archives
Jack-of-all-trades. Analyzing experiment outcomes. Tips for building a DS team. Tidyeval. Presenting data.
Debating Jupyter. Scaling ML at Uber. Cheatsheet for cheatsheets. Learning Python. Skepticism in Data Science. Deep learning from scratch.
🎃 Data Afterlife. Key interview questions. Getting started w/ Airflow. Bokeh 1.0. Slow Learning. MNIST on iOS.
Data Science tech stacks. Julia on GPUs. Info Ops. Choosing better projects. Personality prediction w/ Facebook. Viz through questioning.
Jupyter tips & tricks. Sports analtyics/viz. Mathematics as thought. A Principled Bayesian Workflow. ML optimization tutorial. PDF table extraction.
Blind spots of the data-driven. Hacker's guide to uncertainty. How to deliver on ML projects. State of NLP. A/V from R. Evolving Data PM roles.
Own your data. Leveling-up your ML skills. Why Julia? Custom loss functions. Experimenting w/ SEO. Decision-trees. ML for visualization.
xkcd: Curve Fitting. Fixing ML reproducibility. Matplotlib tips/demos. AI: generating $$ vs saving $$.
Career roadmap. What-If Tool. Data center innovation. Anatomy of an AI. Phases of data analysis. Code as configuration. Boxplots.
Notebook wars. Command line ethics. Why data culture matters. Scaling knowledge w/ graphs. Searching for data. Movie recommendation tutorial.
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