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Data Science Reference Library
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Intro to wavelets. Breathing K-Means. Neural nets from scratch. What to learn. Generative art w/ R.
State of AI 2021. False positives. Bayesian optimization. Covid data glitches. Kernel algorithms. KPIs for machine learning classifiers.
The 2021 Data Landscape. Art of linear algebra. Human regression ensemble. SQLite Playground. Bullshit visualization. Intro to deep learning.
Top places to work. Start w/o Machine Learning. Beyond bar charts. Diminishing returns.
Salary report. Percentile approximation. Horizon Plots for ggplot2. Timezone madness. Modern BI. Participatory data stewardship.
Full stack data science. The Great Resignation. The Puzzle Of football ⚽ Analytics. Media mix modeling. Streaming data machine learning. What's an OLAP cube?
Clever matrices. Best practices for recommenders. Software design for data scientists. Gentle intro to GNNs. Decision Making at Netflix.
Quantifying Interestingness. Lightweight data validation. The data experience. Inferring concept drift. Working with U.S. Census data.
Cheatsheets. Exploring R² w/ diagrams. Similarity search. Machine learning Explained for 5 levels of expertise. How to write clearly.
Too big for RAM. Data science role evolution. Bootstrapping labels. Making better decsions w/ stats. Data quality unpacked. Data platforms.
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