Data Elixir - Data Elixir - Issue 372
ISSUE 372 · February 1, 2022InsightSix Statistical Critiques That Don’t Quite WorkSkepticism about statistics is generally healthy but, just as blind belief can lead you to believe things that aren’t true, an overabundance of skepticism can lead you to disbelieve things that are actually true. Here are six common fallacies to watch out for. We’ve only scratched the surface of the full potential for the data warehouseAlthough it may feel like we’re at the peak of the data warehouse, there's a good argument here that we've barely scratched the surface. Here's how data warehouses are evolving to eventually become the control center for modern companies. Sponsored LinkSolve Your Data Challenges Using AI & Human ExpertiseInnodata offers data annotation, transformation, collection, synthetic generation, and intelligent automation with industry-leading platforms and managed services. With 30+ years of experience and 3,500+ global SMEs, we accelerate operations and advance AI/ML models to help companies scale faster. Get started with Innodata today! Tutorials, Projects & OpinionsExperiment without the wait: Speeding up the iteration cycle with Offline Replay ExperimentationOnline experimentation is often used to evaluate product ideas but it's costly and time-consuming. To help optimize the process, Pinterest developed a framework they call "Offline Relay Experimentation," which helps them predict outcomes without even running an experiment. Here's how it works. A Modern Introduction to Probabilistic ProgrammingProbabilistic programming is a technique for translating mathematical models into executable code. This tutorial is an awesome introduction to how it works, including lots of examples, code samples, and links to important references along the way. A practical intro to Discrete Wavelet TransformationDiscreet wavelet transformations (DWT) can be used to remove noise from a signal, reduce dimensionality of data, and for tasks such as clustering and classification. This interactive post makes it easy to understand how DWT works and how to use it with simple examples. Predicting When Kickers Get Iced with {tidymodels}This step-by-step tutorial explores data from the College Football Database, the modeling process using tidymodels, and how to explain the model using tools such as variable importance plots, partial dependency plots, and SHAP values. If you've been looking for a nice introduction to tidymodels, this is it! Wordle 1/6 🟩🟩🟩🟩🟩Everyone seems to be playing Wordle these days and many post their ⬛🟨🟩 scores on Twitter. There aren't answers in those squares but by using frequency distributions, Ben Hamner explores a clever approach for guessing the correct word on the first attempt — every time. Get training data for ML in record timeDesigned by engineers for engineers, Toloka combines cutting-edge technologies with the power of the crowd to deliver high-performing data for Machine Learning projects in record time. Built-in quality control system provides superb data accuracy at scale. Code & ToolsSpyQL - SQL with Python in the middleSpyQL is a query language that combines the simplicity and structure of SQL with the power and readability of Python. It's lightweight, easy to use and will feel familiar if you already work with Python or SQL. explainerdashboardThis package makes it easy to deploy a web app that explains the inner workings of a (scikit-learn compatible) machine learning model. Provides interactive plots on model performance, feature importances, feature contributions to individual predictions, "what if" analysis, partial dependence plots, SHAP (interaction) values and more. Resources📢 Welcome to ar5iv.orgar5iv offers a modern web view for arXiv's preprints. Change the "X" in any arXiv article link to a "5" and get a modern HTML5 document. This thread walks through what's included, why now, and how the project hopes to merge back into arXiv. To find specific content from prior issues or to research topics, check out the searchable Archives on Data Elixir's Search Page >> |
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Data Elixir - Issue 371
Tuesday, January 25, 2022
Research highlights of 2021. Faster Python. Too much data? SQL alternatives. Mistakes included. AI warfare.
Data Elixir - Issue 370
Tuesday, January 18, 2022
ML: 2021 and beyond. State of ML in Julia. Bayesian Modeling w/ Python. Shiny databases. Lead scoring w/ logistic regression. Beautiful plotting in R.
Data Elixir - Issue 369
Tuesday, January 11, 2022
Tactical career planning. The data-to-engineer ratio. ML generalization. Spiral graphs. DS management: the first year. Interview prep guide.
Data Elixir - Issue 368
Tuesday, January 4, 2022
Top notebooks of 2021. ⚽ Analytics Review. On testing. Real-time ML. ML YouTube.
Data Elixir - Issue 367
Tuesday, December 21, 2021
Top Python libraries in 2021. Essential visualization. Jupyter games. Life of an ML dataset. Data versioning.
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