Recent Issues:
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Issue 426
Awesome Polars. Patterns for content moderation. Fundamentals of data viz. New machine setup for data science. Data-Centric AI.
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Issue 425
2023 data ecosystem. EDA for Jupyter. Data salary benchmark for Europe. Get old code running again. ggplot2 tricks. Creating a data cleaning workflow.
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Issue 424
Big Data is dead. GPT from scratch. How to be incognito in 2023. Sports analytics. Intro to geospatial data.
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Issue 423
Faster A/B decisions. Soccer Analytics Handbook. Getting started with large language models. Floating point problems. Critiquing data visualization.
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Issue 422
Illustrated pandas. Simpson's paradox. How to approach resumes. The GPT analyst. Accelerating A/B tests.
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Issue 421
Crafting a career. Pandas coding assistant. Google Research trends. Data science cheatsheets. Framework for effective machine learning. Proximity analysis.
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Issue 420
Modern Polars. GPT from scratch. Predictions via mixed models. Machine learning for weather and climate. GNU Octave for Jupyter.
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Issue 419
Matrices and graphs. Visualization trends. SQL tells a human story. Combining R and Python. Flow fields tutorial. Machine learning cheatsheets.
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Issue 418
Top Python libraries in 2022. Football ⚽ Analytics Review. How Shapley values work. Spatial data analysis with Python.
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Issue 417
2023 conferences. High-dimensional probability. Breaking the winner's curse. TikTok's recommender secrets. Working with spatial data.
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Issue 416
Unintended biases. Machine learning for Sheets. Data as a product. Understanding convolutions in probability.
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Issue 415
ChatGPT tricks. ML and human-in-the-loop at Airbnb. Distributed SQLite. Modern-day programming. How to become an Analytics Engineer.
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Issue 414
How to build a World Cup betting model. Demystifying Fourier analysis. Data wrangling w/ Julia. Rant from the trenches.
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Issue 413
AR timeseries modeling. Python: good code, bad code. Functional analysis. Advanced NLP. Protecting privacy with federated learning.
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Issue 412
Python+SQL: SpyQL. Forecasting principles and practice. A/B testing caveats and limitations. Bullet graphs. Simplifying MLOps.
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Issue 411
Bayesian structural timeseries. Building data dictionaries. Dashboard design patterns. Visualization w/ Python.
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Issue 410
Data Stack in a Box. Earth System Modeling. Guide to posterior predictions. Data science interview book.
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Issue 409
Monetizing internal tools. Experimentation platform in a day. Quarto Q/A. Quote extraction w/ NLP. Visualizing spatial data w/ Python. State of Open Data 2022.
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Issue 408
State of AI 2022. Exploratory causal analysis. Data testing for Python. Chance encounters. RecSys 2022. Building platforms for DS.
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Issue 407
ML-powered stock picking engine. K-Means Clustering explainer. How to use text in data viz. Counterfactual forecasting.
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Issue 406
Squishy data. Design principles for data analysis. How to explore large datasets. Anomaly detection at scale.
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Issue 405
Linear regression visual explainer. A Sequel to SQL? Correlated features & machine learning models. Is a data leader role right for you?
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Issue 404
Data 'creation' vs. 'extraction.' On being a Data Lead. Categorizing machine learning interpretability approaches. Mapping wind data.
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Issue 403
Semantic layers: a deep dive. Communicating A/B test results. Using an attribution framework. Bayesian age-period-cohort models in Python.
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Issue 402
Modeling and analytics for ⚽. Practical causal forecasting. Intro to data contracts. Expressive analytics w/ Python.
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Issue 401
Homegrown auth w/ machine learning. Intro to backprop. Key-value dbs. GPT-3 for science. Data product canvas. R-spatial ecosystem.
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Issue 400
Deep dive into SVD. Smart paywalls. Idea to funding. Bayesian inference at scale. Logistic regression explainer.
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Issue 399
The 8 slide resume. Intro to streaming for data scientists. Random Forest explainer.
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Issue 398
Building modern data teams. Art From Code. Jupyter for code development & publishing. Data science guide to statistical genetics. Nuanced metrics.
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Issue 397
Guide to sports analytics. Tensor Puzzles 🧩. Betting on data. Deep learning for tabular data. Results vs. Accuracy.
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Issue 396
Coming up with research ideas. Tidy finance. Network analysis. Critical dataset studies. ML engineering.
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Issue 395
Pandas anti-patterns. Python for data analysis. Team size & complexity. Success metrics. MLOps simplified. Data in wonderland. Careers in data viz.
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Issue 394
Causal forecasting. ML exercises for pen & paper. Mixed effects models tutorial. Geo-based A/B testing.
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Issue 393
What Julia gets right. ML stack trends. Scraped data: fair game? Things you should know about DBs. Investment research platform for data science.
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Issue 392
Graph ML. JTBD for data teams. How to get data out of PDFs. Research highlights from Meta. Reproducible research workflows.
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Issue 391
Machine learning design patterns. Awesome data leadership. Faster Pandas. Machine learning experimentation in VS Code.
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Issue 390
Friendlier SQL. Decision Intelligence framework. Collective data rights.
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Issue 389
The technical pay gap. Data Science: Foundations, Challenges, Opportunities. Existential threat of data quality. Machine learning visual explainers.
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Issue 388
Software development for data scientists. How random forests really work. Visualizing multicollinearity. Machine learning for conservation.
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Issue 387
Bandits for recommender systems. Supervised clustering. JavaScript for R. Teaching data science at scale.
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Issue 386
Trusting your data. How to protect your models. How to hire for DS roles. Horizon charts.
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Issue 385
Making data actionable. Using BIG AI models in a startup. From academia to industry. Machine learning validity. Mental models for visualization.
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Issue 384
Null Island. Confidence intervals for machine learning classifiers. Data tests. Containers for machine learning. Performance utilities for regression modeling
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Issue 383
Data teams: embedded or centralized? Unskilled and unaware of it. Counterfactual evaluation. Quant UX vs data science.
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Issue 382
Quarto. Machine learning notebook tutorials. Reproducible & trustworthy workflows. Real-world recommenders. Graph-based outlier detection.
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Issue 381
Causal inference: core methods & tools. How to read papers. Data strategies with regular people. Preferences in recommender systems.
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Issue 380
Emerging data architectures. 200K+ Salaries. Advanced EDA w/ Python. Precision & Recall. ML-based causal inference.
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Issue 379
Hard SQL interview questions. Imbalance detection. Real-world Prophet. Effective data teams. Data science project quick-start. AI trends.
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Issue 378
Open salaries. Foundations of causal inference. Data Apps. Data labelling. Jupyter everywhere.
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Issue 377
ML for design. Embrace complexity. People analytics. MLOps is a mess. Algorithms for Decision Making. The evolving AI startup.
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Issue 376
Active learning. Interpretable models. Probabilistic machine learning: Advanced Topics. Notebooks in production.
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Issue 375
Data diff algorithms. Unbundling the data platform. Changing jobs? Watch for these 🚩🚩. Interactive canvas for Jupyter. Finding missing evidence.
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Issue 374
Intro to design-based causal inference. Easy EDA for Pandas. Modeling with encrypted data. Data distribution shifts.
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Issue 373
How data businesses work. Salaries dropping. Machine learning monitoring research challenges. Python setup for data science. State of Data Visualization.
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Issue 372
Predicting experiments. 🟩🟩🟩🟩🟩. Intro to probabilistic programming. Future of the data warehouse. Bad stat critiques.
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Issue 371
Too much data? Research highlights of 2021. Faster Python. SQL alternatives. Mistakes included. AI warfare.
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Issue 370
ML: 2021 and beyond. State of machine learning in Julia. Bayesian Modeling w/ Python. Shiny databases. Lead scoring w/ logistic regression. Beautiful plotting in R.
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Issue 369
Tactical career planning. The data-to-engineer ratio. Machine learning generalization. Spiral graphs. Data science management: the first year. Interview prep guide.
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Issue 368
Top notebooks of 2021. ⚽ Analytics Review. On testing. Real-time machine learning. Machine Learning on YouTube.
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Issue 367
Top Python libraries in 2021. Jupyter games. Essential visualization. Life of a machine learning dataset. Data versioning.
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Issue 366
Big data paradox. Data 'scientists'...? Machine learning playgrounds. Data serialisation in R. Building models like open-source software.
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Issue 365
Tidy/Pandas visual tutors. State of Open Data. Unit testing in R. Mining the Pandora Papers.
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Issue 364
Shuffling the cloud. Data for good, responsibly. Decision tree viz. Longform NLP pipelines. Controlling the job hunt.
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Issue 363
Transformers from scratch. Open-source experiment tracker. Parameter exploration w/ Bayesian Optimization. Confidential computing.
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Issue 362
Holistic decision-making. ROI of data work. The Data Librarian. Automated root cause analysis. Scientific visualization. When machine learning hates veggies.
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Issue 361
Non-tech guide to interpretable ML. Avoiding data disasters. Beta regression. Measuring success. Better than box plots.
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Issue 360
Data stack enigmas. Survival analysis. Time series regression w/ PyTorch. Survival analysis. Data visualization analysis and design.
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Issue 359
Future of operational analytics. Interpreting A/B tests. Gradient boosted trees for spatial data. Data Viz superpowers. Intro to probability for data science.
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Issue 358
Intro to wavelets. Breathing K-Means. Neural nets from scratch. What to learn. Generative art w/ R.
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Issue 357
State of AI 2021. False positives. Bayesian optimization. Covid data glitches. Kernel algorithms. KPIs for machine learning classifiers.
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Issue 356
The 2021 Data Landscape. Art of linear algebra. Human regression ensemble. SQLite Playground. Bullshit visualization. Intro to deep learning.
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Issue 355
Top places to work. Start w/o Machine Learning. Beyond bar charts. Diminishing returns.
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Issue 354
Salary report. Percentile approximation. Horizon Plots for ggplot2. Timezone madness. Modern BI. Participatory data stewardship.
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Issue 353
Full stack data science. The Great Resignation. The Puzzle Of football ⚽ Analytics. Media mix modeling. Streaming data machine learning. What's an OLAP cube?
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Issue 352
Clever matrices. Best practices for recommenders. Software design for data scientists. Gentle intro to GNNs. Decision Making at Netflix.
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Issue 351
Quantifying Interestingness. Lightweight data validation. The data experience. Inferring concept drift. Working with U.S. Census data.
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Issue 350
Cheatsheets. Exploring R² w/ diagrams. Similarity search. Machine learning Explained for 5 levels of expertise. How to write clearly.
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Issue 349
Too big for RAM. Data science role evolution. Bootstrapping labels. Making better decsions w/ stats. Data quality unpacked. Data platforms.
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Issue 348
📺 Machine Learning YouTube Courses. Data quality at scale. Survival analysis. Intro to statistical learning. Visualizing code. Monetizing data.
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Issue 347
Salary review. Untapped AI. SQL snippets. What's bad about Julia? Fast time-series. How language models understand the world.
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Issue 346
Simple & effective charts. Dirty data. Testing Julia. Regression modeling. Bird call ID w/ machine learning. 30 days of machine learning.
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Issue 345
For SQL. Analytics at a crossroads. Debugging tips & tricks. Retraining ML models. Data for Good landscape.
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Issue 344
Causal inference in the wild. Blazing fast data science. Top 10 ideas in statistics. Beautiful Julia. Against SQL. Self-serve Turing Test.
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Issue 343
Tackling climate change w/ AI. Jupyter unit testing. AI in health care. The data team - a short story. Alien Dreams.
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Issue 342
Sports analytics reading list. Real estate investing with machine learning. Strategy-analytics. Intro to modern stats. What does a data product manager do, exactly?
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Issue 341
Machine learning interviews. Understanding p-values. Applied NLP Thinking. Geospatial data in R. Intro to OpenLineage.
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Issue 340
Intro to data meshes. How-to navigate "expert" advice. Personalization approaches. Linear Algebra for machine learning. Reproducible data science. Geospatial analysis.
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Issue 339
Scaling metrics. Building effective data science teams. Jupyter in a browser. Command line data science. Visualizing distributions. R for public health.
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Issue 338
Agent-based modeling. Life of a CDO. Session-based recommenders. Gaussian process interactive. JavaScript for data analysis. Sandboxed AI.
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Issue 337
Automated data wrangling. Flat Data. Analytics Engineering: the quiet revolution. Machine learning platform lessons. Pitfalls of causal insights.
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Issue 336
Intro to Vector databases. Dagster vs. Airflow. Fast, flexible forecasting. Decision-driven. Visualization by example. Good/Bad data scientist.
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Issue 335
Thinking in data. Spreadsheet munging strategies. Sports analytics w/ AI. Ethics and machine learning licensing. Cluster analysis viz.
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Issue 334
Practical SQL for data analyis. How query-matching works. Metrics at scale. Notebooks evolved: reactive, reproducible, collaborative.
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Issue 333
The Scaling Data Framework. Winning the KY Derby. Metadata analysis vs AI. Computational thinking. Art of mathematics. Missing layer for the modern data stack?
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Issue 332
DataOps. Hire for weaknesses. CLI for Jupyter. Scikit-learn course. Selecting algorithms for time-series forecasting.
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Issue 331
Working w/ data > RAM. Algorithmic bias vs data bias. Exploring network behavior. Keeping up w/ NLP. ggplot2 Geoms. Secure analytics.
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Issue 330
Data monitoring at scale. Model work vs data work. Beyond PCA. Date-time handling for R. Finding signals in the noise.
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Issue 329
Testing notebooks. Intro to PCA. Building an online ad platform. Ghosts in the data. Next-gen apps w/ GPT-3. Platforms vs PhDs.
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Issue 328
Effective data monitoring. Scaling with First Principles. Working with color scales. The Data Journalism Handbook.
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Issue 327
Data pricing. Hands-off anomaly detection. Defensible machine learning. How to write design docs. Understanding instrumental variables estimation. Pattern-based spatial analysis.
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Issue 326
The Modern Analytics Stack. AI trends. Violin plots. Learning path for transformers. The data visualization battleground.
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Issue 325
Gartner: top data trends. Quantified Self infrastructure. Tracking data SLAs. Algorithmic audits. Data coalitions. Feature stores - a hierarchy of needs.
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Issue 324
Data Mesh 101. Data science podcasts. Differential privacy. Level-up your ggplot2 skills. Autodata tools. AI on the battlefield.
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Issue 323
Python surprises. Building the modern data stack. How to build data quality monitors w/ SQL. Supercharging Superset. Fixing the data science talent shortage.
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Issue 322
Metadata's evolving role. Machine learning science fiction. Inside a hot-button research paper 🦜. Remote pair programming with R. TinyML fundmentals.
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Issue 321
Causal design patterns. Why machine learning is hard to tune. Experimentation guardrails. Python EDA toolkit. COVID-19 modeling lessons. How to cite data sources.
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Issue 320
Data monitoring at scale. AI for Good: for REAL? Legal questions for data science. Why business intuition > machine learning. Density plots. Internal tool design.
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Issue 319
Data science as Atomic Habit. Elegant SQL w/ R. Bayesian statistics Primer. Julia update: Python challenger? Best-of Python machine learning. Notes from NeurIPS 2020.
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Issue 318
Real-time machine learning in practice. Search tool for obscure datasets. Intro to probablistic machine learning. Python data validation.
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Issue 317
Top Python libraries for data science. ⚽ Analytics 2020 Review. Uncertainty Toolbox. Real-time machine learning. Medicine's machine learning Problem. Dark data.
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Issue 316
Code reviews for Jupyter. How models leak data. Advanced Data Science 2020. Algorithmic bias: past, present, future. End-to-end machine learning monitoring.
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Issue 315
Data quality at scale. Key statistical ideas of past 50 years. Beautiful plotting w/ ggplot2. 2020 top papers. Distill for R Markdown.
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Issue 314
Machine learning case studies. Least squares as springs. Ensuring data quality. Open data in 2020. Version control for machine learning.
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Issue 313
🔥 Machine learning tutorial w/ crypto. ⚽ Analytics 2021. Dynamic data testing. Modeling vaccination strategies. Experimentation w/ resource constraints.
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Issue 312
Hands-on machine learning. COVID mobility modeling. Prediction markets vs polls. Julia Notebooks. Colliding worlds of BI and DS. Machine learning for Java. Data discovery at Uber
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Issue 311
Selective attention in data analysis. Linear algebra intro & reference. Rebuilding for data quality. Hierarchical time series modeling. Data Feminism.
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Issue 310
U.S. politics w/ R. Data discovery platforms. Bayesian time series modeling. Scalable time series. Form extraction. Mixed models w/ R.
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Issue 309
Hype Cycles. Intro to feature stores. Key interview questions. Data team organization. Machine learning course recommendations. PandasGUI for dataframes.
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Issue 308
Superlearning. Modern data infrastructure. Dockerfile security. Structural time series. Awesome Data Engineering. In AI We Trust.
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Issue 307
Intro to Bayesian Modeling. Strategic career development. Putting machine learning in production. Top research areas for data science. People analytics. Data discovery.
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Issue 306
How to waste your career. 2020 Data & AI Landscape. Why analytics fail. Scaling machine learning. Cardinal rules of stats. Healthy data pipelines.
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Issue 305
Data tooling trends. Recommender Systems. Intro to NumPy and Matplotlib. Red flags for interviews. Hardware Lottery. Data quality governance.
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Issue 304
The cost of privacy. Coding for 🏈 ⚾ ⚽ 🏒 🏀. Randomized responses. Tidy Modeling. Practical intakes. Programming with NumPy.
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Issue 303
Incredible PyT🔥rch. R Markdown Cookbook. Cleaning data. How-to win Kaggle competitions. Communicating w/ Interactives. Model explainability at scale.
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Issue 302
⚽️ Modeling. Election forecasting. COVID-19 broke our models. Predicting traffic. SQL style guide. Visualizing uncertainty.
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Issue 301
Puzzling visualizations. Election forecasting. Practical COVID risk assessment. Big Book of R. Tidyverse-style EDA in Python.
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Issue 300
Testing machine learning. Practical ethics. Data science talent strategy. Visualization Mirages. Machine learning survey papers. Data semantics. Language of Science.
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Issue 299
Generalists vs. specialists. Jupyter Book. Economics of AI. Computational Causal Inference. AG machine learning. Data analysis w/ JavaScript.
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Issue 298
Data Team ROI. Git for data? Multi-armed bandits. Unbundling data science Workflows. 2020 conferences. Dashboarding.
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Issue 297
SQL tricks. Modeling 🏀. Metadata management. Science Fictions. Data validation lib for pandas. Awesome GPT-3.
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Issue 296
Applied machine learning. Faking news. COVID-19: Behind the numbers. Monitoring machine learning. Azure Architectures. Assessing data advantage for AI.
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Issue 295
Advanced SQL. How to choose what to work on. GPT-3. Intro to PyTorch. Inside Palantir. Critiquing data visualization.
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Issue 294
Awesome ML/AI. Large scale experimentation. Simplifying machine learning on time series. Data Infrastructure at Netflix. FAX: the painful bottleneck. Full stack deep learning.
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Issue 293
Making machine learning useful. Learning R. Scalable dashboards. Paper Projects. COVID's misunderstood metric. Engineering foundations. When autonomous systems fail.
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Issue 292
Time series analysis. Building an AI Trading System. Power Tips for Colab. Collider bias. Will demand for data science hold up in a falling economy?
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Issue 291
Machine learning tools landscape. Data-driven healthcare. GitHub Actions for DS/ML. Getting started w/ TensorFlow & Keras. Visualization for colorblind.
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Issue 290
Fighting an epidemic w/ data. Connected papers. New database tech. Scrum for data science. Truncating the y-axis.
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Issue 289
Succeeding in production. Dirty cops. Harnessing creativity. Federated learning. Typography for data visualization.
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Issue 288
Practical Python. Ultimate guide to machine learning deployment. Visualizing reality. Advanced Statistical Computing w/ R. How-to create interactive tutorials.
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Issue 287
📊+❤️. Machine learning Best Practices. Evaluating metrics. Differential privacy. Monitoring Data Quality at Scale. Learning data visualization.
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Issue 286
25 hot new tools. Advanced SQL. Supervised machine learning case studies. Practical A/B testing. Scrollytelling tutorial. AI in healthcare.
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Issue 285
Feature Stores. Black box optimization. Measuring fairness. Streaks w/ Python. Prediction is hard. Keeping track of the apps that track you.
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Issue 284
Leveling-up w/ SQL. Making sense of COVID-19 models. Deploying machine learning data. Setting up a laptop for data science work. Tornado plots. Machine learning in moderation.
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Issue 283
Recommender Systems. What you should know about databases. Automatic code cleaning. Stanford CS229: Machine Learning. Game Boy emulator. Uncertainty visualization. 3D maps.
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Issue 282
Forecasting s-curves. Linear Algebra Done Right. Backpropagation 101. Estimating Rt. Upset plots. Visualizing uncertainty. Machine Learning Interpretability.
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Issue 281
A Life in Games. On-campus w/ COVID-19. Grammar of Tables. Monitoring machine learning. Peer reviews for data science. Oceans of data.
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Issue 280
⚽ Analytics Handbook. Product management for AI. Forecasting Best Practices. Bayesian Data Analysis. scikit-learn tips. Machine learning development platforms.
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Issue 279
Technical freelancing. Julia review. Jupyter visual debugger. Stanford CS472: Data Science for COVID-19. Privacy & pandemics. ggplot2 workshop.
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Issue 278
Data hygiene. Sports analytics book recommendations. Forecasting pandemics in the real world. Retrospective of an AI startup crash.
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Issue 277
Faster R. Liquidity modeling in real estate. End-to-End machine learning tutorial. Evolutionary machine learning.
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Issue 276
Covid-19: Models, notebooks, dashboards, visualizations considerations, data sources and more.
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Issue 275
How to know when an epidemic will end. Creating a data science first organization. Epidemiology with R. Getting data out of PDFs. Visualization grammar.
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Issue 274
Crash course in game theory for machine learning. Mining a data trove with PDFs, email, Word, etc. Data discovery at Spotify. Observable for Jupyter users.
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Issue 273
Making data valuable. Gartner Magic Quadrant for Data Science & Machine Learning. Mathematics for the adventurous self-learner. Computer vision basics in Excel. Reading club.
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Issue 272
Python machine learning trends & developments. The business of AI. Projects to know. What makes machine learning reproducible? Communicating model uncertainty.
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Issue 271
How to predict an epidemic. What does a CDO really do? Finding patterns in high-dimensional data. Data maturity levels. AI trends for 2020. D3 gallery.
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Issue 270
Modeling coronavirus. How to put R in production. Ray tips & tricks. Mathematics for machine learning. Finding your way in machine learning. Distrusting data.
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Issue 269
Notebook pains and opportunities. How to get into sports analytics. Nature of intelligence. Bayesian product ranking. Understanding Altair.
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Issue 268
Answers from data you can't see. Smarter than the market. Cool projects w/ spotifyr. On being self-taught.
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Issue 267
Overfitting: A Guided Tour. Data project checklist. Learning machine learning. Optimizing sample sizes in A/B testing. Chess w/ GPT-2. On data science consulting.
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Issue 266
Intro to autoencoders. Move predictions to your db. ML/NLP research summaries. Modeling salary and gender. Why R? Bayesian inference. Sheets-fu.
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Issue 265
Practical decision-making w/ causality. SQL for data science. Lacking uncertainty. Urban sensing. Efficient computation w/ R. NLP best practices.
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Issue 264
Top data science Python libs of 2019. Reusable data workflows for polyglot teams. Machine unlearning. Data valuation. AI Index Report.
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Issue 263
Probability Distribution Explorer. Why machine learning can't save NFL. Working w/ 100GB+ datasets on a laptop. Data science salaries around world. Vega-Lite 4.0.
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Issue 262
End to end Jupyter. Kubernetes intro. Machine learning trading system. Visual intro to BERT. ~Git for data. Curse of expertise. Privacy vs data.
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Issue 261
⚽ Team formation analysis. Machine learning systems design. Quantitative finance notebooks. Cost-benefit analysis. Local-first data. Audio analysis w/ machine learning.
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Issue 260
Key ML/NLP paper summaries. Confident Learning. Data trends in tech. Journalism AI. Better visualization for science.
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Issue 259
Machine learning product dev. Modern SQL. Scaling a data team. Data discovery. Probablistic scripts. Scientific visualization w/ openGL. Bar chart race tutorial.
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Issue 258
Clean code. Bloom filters. Project Silica. Understanding UMAP. Structuring data teams. Data map challenge. U.S. vs privacy.
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Issue 257
Beyond Jupyter. Killer app for machine learning. Measuring success. Adversarial machine learning. Glue work. How to choose visualization types. Spark w/ R.
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Issue 256
Salaries. Algorithmic slammer. Predicting time-series. SQL query steps. Machine learning portfolio tips. Real-time machine learning at scale. Fake news ID.
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Issue 255
Sports Visualization Digest. Predictive tex . Benchmarking open machine learning models. Crash Course: TensorFlow 2.0 + Keras. Machine learning lessons learned. Data wrangling w/ R.
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Issue 254
Thinking through SQL. Winning ⚽ w/ network science. Probability intuition. Streamlit. MLOps Tooling. Learning w/ time series. Trusting AI.
No spam, ever.