Канал: Data Science Learning Community Videos

Mastering Shiny: Tidy evaluation (mshiny07 12)

Mastering Shiny: Tidy evaluation (mshiny07 12)

Python for Data Analysis: Data Aggregation and Group Operations: Part I (py4da02 10)

Python for Data Analysis: Data Aggregation and Group Operations: Part I (py4da02 10)

Advanced R: Base types (advr09 12)

Advanced R: Base types (advr09 12)

ggplot2: Elegant Graphics for Data Analysis: Maps (ggplot201 6)

ggplot2: Elegant Graphics for Data Analysis: Maps (ggplot201 6)

The Effect: An Introduction to Research Design and Causality: Causal Diagrams (effect01 6)

The Effect: An Introduction to Research Design and Causality: Causal Diagrams (effect01 6)

Mastering Shiny: Bookmarking (mshiny07 11)

Mastering Shiny: Bookmarking (mshiny07 11)

Spatial Statistics: Complete spatial randomness & Spatial point processes (spacestats06 20 19)

Spatial Statistics: Complete spatial randomness & Spatial point processes (spacestats06 20 19)

Advanced R: Function operators (advr09 11)

Advanced R: Function operators (advr09 11)

Practical Deep Learning for Coders: Collaborative filtering (pdl01 7)

Practical Deep Learning for Coders: Collaborative filtering (pdl01 7)

ggplot2: Elegant Graphics for Data Analysis: Statistical summaries (ggplot201 5)

ggplot2: Elegant Graphics for Data Analysis: Statistical summaries (ggplot201 5)

The Effect: An Introduction to Research Design and Causality: Identification (effect01 5)

The Effect: An Introduction to Research Design and Causality: Identification (effect01 5)

Mastering Shiny: Dynamic UI (mshiny07 10)

Mastering Shiny: Dynamic UI (mshiny07 10)

Advanced R: Function factories (advr09 10)

Advanced R: Function factories (advr09 10)

ggplot2: Elegant Graphics for Data Analysis: Collective geoms (ggplot201 4)

ggplot2: Elegant Graphics for Data Analysis: Collective geoms (ggplot201 4)

Practical Deep Learning for Coders: Random forests (pdl01 6)

Practical Deep Learning for Coders: Random forests (pdl01 6)

The Effect: Describing Variables & Describing Relationships (effect01 3 4)

The Effect: Describing Variables & Describing Relationships (effect01 3 4)

Mastering Shiny: Uploads and downloads (mshiny07 9)

Mastering Shiny: Uploads and downloads (mshiny07 9)

Python for Data Analysis: Plotting and Visualization: Part II (py4da02 9)

Python for Data Analysis: Plotting and Visualization: Part II (py4da02 9)

Advanced R: Functionals (advr09 9)

Advanced R: Functionals (advr09 9)

Practical Deep Learning for Coders: From-scratch model (pdl01 5)

Practical Deep Learning for Coders: From-scratch model (pdl01 5)

ggplot2: Elegant Graphics for Data Analysis: Individual geoms (ggplot201 3)

ggplot2: Elegant Graphics for Data Analysis: Individual geoms (ggplot201 3)

The Effect: Designing Research & Research Questions (effect01 1 2)

The Effect: Designing Research & Research Questions (effect01 1 2)

Mastering Shiny: User feedback (mshiny07 8)

Mastering Shiny: User feedback (mshiny07 8)

Python for Data Analysis: Plotting and Visualization (py4da02 9)

Python for Data Analysis: Plotting and Visualization (py4da02 9)

R for Data Science: Quarto formats (r4ds10 29)

R for Data Science: Quarto formats (r4ds10 29)

ggplot2: Elegant Graphics for Data Analysis: First steps (ggplot201 2)

ggplot2: Elegant Graphics for Data Analysis: First steps (ggplot201 2)

The Effect: An Introduction to Research Design and Causality: Introduction (effect01 1)

The Effect: An Introduction to Research Design and Causality: Introduction (effect01 1)

R for Data Science: Quarto (r4ds10 28)

R for Data Science: Quarto (r4ds10 28)

DSLC Project Club: faketables & Facilitator Training (proj01)

DSLC Project Club: faketables & Facilitator Training (proj01)

Spatial Statistics: The spatstat package & Spatial point patterns (spacestats06 18 17)

Spatial Statistics: The spatstat package & Spatial point patterns (spacestats06 18 17)

Advanced R: Conditions (advr09 8)

Advanced R: Conditions (advr09 8)

Practical Deep Learning for Coders: Natural Language (NLP) (pdl01 4)

Practical Deep Learning for Coders: Natural Language (NLP) (pdl01 4)

ggplot2: Elegant Graphics for Data Analysis: Introduction (ggplot201 1)

ggplot2: Elegant Graphics for Data Analysis: Introduction (ggplot201 1)

Introduction to Statistical Learning Using R: Multiple Testing (islr06 13)

Introduction to Statistical Learning Using R: Multiple Testing (islr06 13)

Mastering Shiny: Graphics (mshiny07 7)

Mastering Shiny: Graphics (mshiny07 7)

Advanced R: Environments (advr09 7)

Advanced R: Environments (advr09 7)

Mastering Shiny: Performance (mshiny06 23)

Mastering Shiny: Performance (mshiny06 23)

Mastering Shiny: Layout, themes, HTML (mshiny07 6)

Mastering Shiny: Layout, themes, HTML (mshiny07 6)

Introduction to Statistical Learning Using R: Multiple Testing (islr06 13)

Introduction to Statistical Learning Using R: Multiple Testing (islr06 13)

Mastering Shiny: Security (mshiny06 22)

Mastering Shiny: Security (mshiny06 22)

Spatial Stats for Data Science: Methods assessment & Model-based geostatistics (spacestats06 16 15)

Spatial Stats for Data Science: Methods assessment & Model-based geostatistics (spacestats06 16 15)

Python for Data Analysis: Data Wrangling: Join, Combine, and Reshape: Part II (py4da02 8)

Python for Data Analysis: Data Wrangling: Join, Combine, and Reshape: Part II (py4da02 8)

Advanced R: Functions (advr09 6)

Advanced R: Functions (advr09 6)

Practical Deep Learning for Coders: Neural net foundations (pdl01 3)

Practical Deep Learning for Coders: Neural net foundations (pdl01 3)

Introduction to Statistical Learning Using R: Unsupervised Learning (islr06 12)

Introduction to Statistical Learning Using R: Unsupervised Learning (islr06 12)

Mastering Shiny: Workflow (mshiny07 5)

Mastering Shiny: Workflow (mshiny07 5)

Advanced R: Control flow (advr09 5)

Advanced R: Control flow (advr09 5)

Explanatory Model Analysis: FIFA 19 (ema01 21)

Explanatory Model Analysis: FIFA 19 (ema01 21)

Python for Data Analysis: Data Wrangling: Join, Combine, and Reshape: Part I (py4da02 8)

Python for Data Analysis: Data Wrangling: Join, Combine, and Reshape: Part I (py4da02 8)

R for Data Science: A field guide to base R (r4ds10 27)

R for Data Science: A field guide to base R (r4ds10 27)

Web APIs with R: Find APIs & Communicate with other types of APIs (wapir01 10 11)

Web APIs with R: Find APIs & Communicate with other types of APIs (wapir01 10 11)

Practical Deep Learning for Coders: Deployment (pdl01 2)

Practical Deep Learning for Coders: Deployment (pdl01 2)

Mastering Shiny: Case study: ER injuries (mshiny07 4)

Mastering Shiny: Case study: ER injuries (mshiny07 4)

Mastering Shiny: Testing (mshiny06 21)

Mastering Shiny: Testing (mshiny06 21)

Explanatory Model Analysis: Summary of Dataset-level Exploration (ema01 20)

Explanatory Model Analysis: Summary of Dataset-level Exploration (ema01 20)

R for Data Science: Iteration (r4ds10 26)

R for Data Science: Iteration (r4ds10 26)

Advanced R: Subsetting (advr09 4)

Advanced R: Subsetting (advr09 4)

Advanced R: Function operators (advr08 11)

Advanced R: Function operators (advr08 11)

Practical Deep Learning for Coders: Getting started (pdl01 1)

Practical Deep Learning for Coders: Getting started (pdl01 1)

Web APIs with R: Do other things with APIs (wapir01 9)

Web APIs with R: Do other things with APIs (wapir01 9)

Introduction to Statistical Learning Using R: Unsupervised Learning (islr06 12)

Introduction to Statistical Learning Using R: Unsupervised Learning (islr06 12)

Mastering Shiny: Basic Reactivity (mshiny07 3)

Mastering Shiny: Basic Reactivity (mshiny07 3)

Mastering Shiny: Packages (mshiny06 20)

Mastering Shiny: Packages (mshiny06 20)

Explanatory Model Analysis: Residual-diagnostics Plots (ema01 19)

Explanatory Model Analysis: Residual-diagnostics Plots (ema01 19)

DSLC Project Club: CascadiaRConf Talks (proj01)

DSLC Project Club: CascadiaRConf Talks (proj01)

Spatial Statistics for Data Science: Theory and Practice with R: Kriging (spacestats06 14)

Spatial Statistics for Data Science: Theory and Practice with R: Kriging (spacestats06 14)

R for Data Science: Functions (r4ds10 25)

R for Data Science: Functions (r4ds10 25)

Advanced R: Vectors (advr09 3)

Advanced R: Vectors (advr09 3)

Advanced R: Function factories (advr08 10)

Advanced R: Function factories (advr08 10)

Web APIs with R: Scrape data from web pages (wapir01 7)

Web APIs with R: Scrape data from web pages (wapir01 7)

Introduction to Statistical Learning Using R: Survival Analysis and Censored Data (islr06 11)

Introduction to Statistical Learning Using R: Survival Analysis and Censored Data (islr06 11)

Mastering Shiny: Basic UI (mshiny07 2)

Mastering Shiny: Basic UI (mshiny07 2)

Probabilistic Machine Learning: An Introduction: Logistic Regression (second half) (pml01 10)

Probabilistic Machine Learning: An Introduction: Logistic Regression (second half) (pml01 10)

R Packages: Q&A with Jenny Bryan (rpkgs06 author)

R Packages: Q&A with Jenny Bryan (rpkgs06 author)

Python for Data Analysis: Plotting and Visualization (py4da02 9)

Python for Data Analysis: Plotting and Visualization (py4da02 9)

Spatial Statistics for Data Science: Spatial interpolation methods (spacestats06 13)

Spatial Statistics for Data Science: Spatial interpolation methods (spacestats06 13)

R for Data Science: Web scraping (r4ds10 24)

R for Data Science: Web scraping (r4ds10 24)

Advanced R: Names and values (advr09 2)

Advanced R: Names and values (advr09 2)

Introduction to Statistical Learning Using R: Survival Analysis and Censored Data (islr06 11)

Introduction to Statistical Learning Using R: Survival Analysis and Censored Data (islr06 11)

Mastering Shiny: Your first Shiny app (mshiny07 1)

Mastering Shiny: Your first Shiny app (mshiny07 1)

Probabilistic Machine Learning: An Introduction: Logistic Regression (first half) (pml01 10)

Probabilistic Machine Learning: An Introduction: Logistic Regression (first half) (pml01 10)

Explanatory Model Analysis: Local-dependence and Accumulated-local Profiles (ema01 18)

Explanatory Model Analysis: Local-dependence and Accumulated-local Profiles (ema01 18)

R for Data Science: Hierarchical data (r4ds10 23)

R for Data Science: Hierarchical data (r4ds10 23)

Advanced R: Introduction (advr09 1)

Advanced R: Introduction (advr09 1)

Web APIs with R: Process other response types (wapir01 7)

Web APIs with R: Process other response types (wapir01 7)

Probabilistic Machine Learning: An Introduction: Linear Discriminant Analysis (pml01 9)

Probabilistic Machine Learning: An Introduction: Linear Discriminant Analysis (pml01 9)

R Packages: Releasing to CRAN (rpkgs06 22)

R Packages: Releasing to CRAN (rpkgs06 22)

Mastering Shiny: Shiny modules (mshiny06 19)

Mastering Shiny: Shiny modules (mshiny06 19)

Spatial Statistics for Data Science: Geostatistical data (spacestats01 12)

Spatial Statistics for Data Science: Geostatistical data (spacestats01 12)

Python for Data Analysis: Data Cleaning and Preparation (py4da02 7)

Python for Data Analysis: Data Cleaning and Preparation (py4da02 7)

Probabilistic Machine Learning: An Introduction: Linear Discriminant Analysis (pml01 9)

Probabilistic Machine Learning: An Introduction: Linear Discriminant Analysis (pml01 9)

R Packages: Lifecycle (rpkgs06 21)

R Packages: Lifecycle (rpkgs06 21)

Explanatory Model Analysis: Partial-dependence Profiles (ema01 17)

Explanatory Model Analysis: Partial-dependence Profiles (ema01 17)

Python for Data Analysis: Data Loading, Storage, and File Formats: Part II (py4da02 6)

Python for Data Analysis: Data Loading, Storage, and File Formats: Part II (py4da02 6)

R for Data Science: Arrow (r4ds10 22)

R for Data Science: Arrow (r4ds10 22)

Advanced R: Functionals (advr08 9)

Advanced R: Functionals (advr08 9)

Web APIs with R: How do I tell the API who I am? (wapir01 6)

Web APIs with R: How do I tell the API who I am? (wapir01 6)

Probabilistic Machine Learning: An Introduction: Foundations (pml01 1)

Probabilistic Machine Learning: An Introduction: Foundations (pml01 1)

R Packages: Software development practices (rpkgs06 20)

R Packages: Software development practices (rpkgs06 20)

ISLR: Deep Learning (islr06 10)

ISLR: Deep Learning (islr06 10)

Spatial Statistics for Data Science: Disease risk modeling & Areal data issues (spacestats01 10 11)

Spatial Statistics for Data Science: Disease risk modeling & Areal data issues (spacestats01 10 11)

Explanatory Model Analysis: Variable-importance Measures (ema01 16)

Explanatory Model Analysis: Variable-importance Measures (ema01 16)

Python for Data Analysis: Data Loading, Storage, and File Formats: Part I (py4da02 6)

Python for Data Analysis: Data Loading, Storage, and File Formats: Part I (py4da02 6)

R for Data Science: Databases (r4ds10 21)

R for Data Science: Databases (r4ds10 21)

Advanced R: Conditions (advr08 8)

Advanced R: Conditions (advr08 8)

Web APIs with R: How do I tell the API who I am? (wapir01 6)

Web APIs with R: How do I tell the API who I am? (wapir01 6)

R Packages: Website (rpkgs06 19)

R Packages: Website (rpkgs06 19)

ISLR: Deep Learning (islr06 10)

ISLR: Deep Learning (islr06 10)

R for Data Science: Quarto formats (r4ds09 29)

R for Data Science: Quarto formats (r4ds09 29)

EMA: Intro to Dataset-level Exploration & Model-performance Measures (ema01 14 15)

EMA: Intro to Dataset-level Exploration & Model-performance Measures (ema01 14 15)

Python for Data Analysis: Getting Started with pandas: Part II (py4da02 5)

Python for Data Analysis: Getting Started with pandas: Part II (py4da02 5)

Spatial Statistics for Data Science: Bayesian spatial models (spacestats01 9)

Spatial Statistics for Data Science: Bayesian spatial models (spacestats01 9)

R for Data Science: Spreadsheets (r4ds10 20)

R for Data Science: Spreadsheets (r4ds10 20)

Advanced R: Functions - part II & Environments (advr08 6 7)

Advanced R: Functions - part II & Environments (advr08 6 7)

Web APIs with R: How can I get a lot of data from an API? (wapir01 5)

Web APIs with R: How can I get a lot of data from an API? (wapir01 5)

ISLR: Support Vector Machines (islr06 9)

ISLR: Support Vector Machines (islr06 9)

R Packages: Other markdown files (rpkgs06 18)

R Packages: Other markdown files (rpkgs06 18)

R for Data Science: Quarto (r4ds09 28)

R for Data Science: Quarto (r4ds09 28)

Mastering Shiny: Functions (mshiny06 18)

Mastering Shiny: Functions (mshiny06 18)

Explanatory Model Analysis: Summary of Instance-level Exploration (ema01 13)

Explanatory Model Analysis: Summary of Instance-level Exploration (ema01 13)

Python for Data Analysis: Getting Started with pandas: Part I (py4da02 5)

Python for Data Analysis: Getting Started with pandas: Part I (py4da02 5)

DSLC Project Club: ShinyConf Talks (proj01)

DSLC Project Club: ShinyConf Talks (proj01)

R Packages: Vignettes (rpkgs06 17)

R Packages: Vignettes (rpkgs06 17)

ISLR: Support Vector Machines (islr06 9)

ISLR: Support Vector Machines (islr06 9)

R for Data Science: A field guide to base R (r4ds09 27)

R for Data Science: A field guide to base R (r4ds09 27)

Mastering Shiny: General guidelines (mshiny06 17)

Mastering Shiny: General guidelines (mshiny06 17)

Explanatory Model Analysis: Ceteris-paribus Oscillations (ema01 12)

Explanatory Model Analysis: Ceteris-paribus Oscillations (ema01 12)

ISLP: Multiple Testing (islp01 13)

ISLP: Multiple Testing (islp01 13)

R for Data Science: Joins (r4ds10 19)

R for Data Science: Joins (r4ds10 19)

Web APIs with R: httr2 introduction & How can I get a lot of data from an API? (wapir01 4 5)

Web APIs with R: httr2 introduction & How can I get a lot of data from an API? (wapir01 4 5)

ISLR: Tree-Based Methods (islr06 8)

ISLR: Tree-Based Methods (islr06 8)

R for Data Science: Iteration (r4ds09 26)

R for Data Science: Iteration (r4ds09 26)

Mastering Shiny: Escaping the graph (mshiny06 16)

Mastering Shiny: Escaping the graph (mshiny06 16)

Explanatory Model Analysis: Ceteris-paribus Oscillations (ema01 11)

Explanatory Model Analysis: Ceteris-paribus Oscillations (ema01 11)

ISLP: Multiple Testing (islp01 13)

ISLP: Multiple Testing (islp01 13)

Spatial Statistics for Data Science: Spatial autocorrelation (spacestats01 8)

Spatial Statistics for Data Science: Spatial autocorrelation (spacestats01 8)

R for Data Science: Missing values (r4ds10 18)

R for Data Science: Missing values (r4ds10 18)

Advanced R: Functions - part I (advr08 6)

Advanced R: Functions - part I (advr08 6)

Web APIs with R: How can I quickly parse API responses? (wapir01 3)

Web APIs with R: How can I quickly parse API responses? (wapir01 3)

R Packages: Function documentation (rpkgs06 16)

R Packages: Function documentation (rpkgs06 16)

ISLR: Tree-Based Methods (islr06 8)

ISLR: Tree-Based Methods (islr06 8)

R for Data Science: Functions (r4ds09 25)

R for Data Science: Functions (r4ds09 25)

Spatial Statistics for Data Science: Spatial neighborhood matrices (spacestats01 7)

Spatial Statistics for Data Science: Spatial neighborhood matrices (spacestats01 7)

DSLC Project Club: climbwith.info (proj01)

DSLC Project Club: climbwith.info (proj01)

R for Data Science: Dates and times (r4ds10 17)

R for Data Science: Dates and times (r4ds10 17)

Advanced R: Control flow (advr08 5)

Advanced R: Control flow (advr08 5)

Learning Statistics with R: Linear regression. (lsr01 15)

Learning Statistics with R: Linear regression. (lsr01 15)

ISLR: Moving Beyond Linearity (islr06 7)

ISLR: Moving Beyond Linearity (islr06 7)

R Packages: Advanced testing techniques (rpkgs06 15)

R Packages: Advanced testing techniques (rpkgs06 15)

ISLP: Unsupervised Learning (islp01 12)

ISLP: Unsupervised Learning (islp01 12)

Explanatory Model Analysis: Ceteris-paribus Profiles (ema01 10)

Explanatory Model Analysis: Ceteris-paribus Profiles (ema01 10)

Mastering Shiny: Reactive building blocks (mshiny06 15)

Mastering Shiny: Reactive building blocks (mshiny06 15)

Spatial Statistics for Data Science: R packages to download open spatial data (spacestats01 6)

Spatial Statistics for Data Science: R packages to download open spatial data (spacestats01 6)

R for Data Science: Factors (r4ds10 16)

R for Data Science: Factors (r4ds10 16)

Advanced R: Subsetting (advr08 4)

Advanced R: Subsetting (advr08 4)

Fundamentals of Numerical Computation: Two-dimensional problems (fnc01 13)

Fundamentals of Numerical Computation: Two-dimensional problems (fnc01 13)

Web APIs with R: How can I get started with APIs? Part 2 (wapir01 2)

Web APIs with R: How can I get started with APIs? Part 2 (wapir01 2)

Deep R Programming: Unevaluated expressions (*) (deepr01 15)

Deep R Programming: Unevaluated expressions (*) (deepr01 15)

R Packages: Designing your test suite (rpkgs06 14)

R Packages: Designing your test suite (rpkgs06 14)

ISLR: Linear Model Selection and Regularization (islr06 6)

ISLR: Linear Model Selection and Regularization (islr06 6)

R for Data Science: Web scraping (r4ds09 24)

R for Data Science: Web scraping (r4ds09 24)

Explanatory Model Analysis: Local Interpretable Model-agnostic Explanations (LIME) (ema01 9)

Explanatory Model Analysis: Local Interpretable Model-agnostic Explanations (LIME) (ema01 9)

Spatial Statistics for Data Science: Making maps with R (spacestats01 5)

Spatial Statistics for Data Science: Making maps with R (spacestats01 5)

Python for Data Analysis: Appendix A. Advanced NumPy: Part 2 (py4da02 A)

Python for Data Analysis: Appendix A. Advanced NumPy: Part 2 (py4da02 A)

R for Data Science: Regular expressions (r4ds10 15)

R for Data Science: Regular expressions (r4ds10 15)

Advanced R: Vectors (advr08 3)

Advanced R: Vectors (advr08 3)

Web APIs with R: How can I get started with APIs? (wapir01 2)

Web APIs with R: How can I get started with APIs? (wapir01 2)

Deep R Programming: Interfacing compiled code (**) (deepr01 14)

Deep R Programming: Interfacing compiled code (**) (deepr01 14)

R Packages: Testing basics (rpkgs06 13)

R Packages: Testing basics (rpkgs06 13)

ISLR: Linear Model Selection and Regularization (islr06 6)

ISLR: Linear Model Selection and Regularization (islr06 6)

R for Data Science: Hierarchical data (r4ds09 23)

R for Data Science: Hierarchical data (r4ds09 23)

Explanatory Model Analysis: Shapley Additive Explanations (SHAP) for Average Attributions (ema01 8)

Explanatory Model Analysis: Shapley Additive Explanations (SHAP) for Average Attributions (ema01 8)

ISLP: Unsupervised Learning (islp01 12)

ISLP: Unsupervised Learning (islp01 12)

Python for Data Analysis: Appendix A. Advanced NumPy: Part 1 (py4da02 A)

Python for Data Analysis: Appendix A. Advanced NumPy: Part 1 (py4da02 A)

R4DS Project Club: ggactivity (proj01)

R4DS Project Club: ggactivity (proj01)

Spatial Statistics for Data Science: The terra package for raster and vector data (spacestats01 4)

Spatial Statistics for Data Science: The terra package for raster and vector data (spacestats01 4)

R for Data Science: Strings (r4ds10 14)

R for Data Science: Strings (r4ds10 14)

Fundamentals of Numerical Computation: Advection equations (fnc01 12)

Fundamentals of Numerical Computation: Advection equations (fnc01 12)

Deep R Programming: Graphics (deepr01 13)

Deep R Programming: Graphics (deepr01 13)

R Packages: Licensing (rpkgs06 12)

R Packages: Licensing (rpkgs06 12)

ISLR: Resampling Methods (islr06 5)

ISLR: Resampling Methods (islr06 5)

Mastering Shiny: The reactive graph (mshiny06 14)

Mastering Shiny: The reactive graph (mshiny06 14)

R for Data Science: Arrow (r4ds09 22)

R for Data Science: Arrow (r4ds09 22)

Explanatory Model Analysis: Break-down Plots for Interactions (ema01 7)

Explanatory Model Analysis: Break-down Plots for Interactions (ema01 7)

ISLP: Survival Analysis and Censored Data (islp01 11)

ISLP: Survival Analysis and Censored Data (islp01 11)

Advanced R: Names and values (advr08 2)

Advanced R: Names and values (advr08 2)

Fundamentals of Numerical Computation: Diffusion equations (fnc01 11)

Fundamentals of Numerical Computation: Diffusion equations (fnc01 11)

R Packages: Dependencies: In Practice (rpkgs06 11)

R Packages: Dependencies: In Practice (rpkgs06 11)

ISLR: Resampling Methods (islr06 5)

ISLR: Resampling Methods (islr06 5)

Python for Data Analysis: NumPy Basics: Arrays and Vectorized Computation: Part 2 (py4da02 4)

Python for Data Analysis: NumPy Basics: Arrays and Vectorized Computation: Part 2 (py4da02 4)

Spatial Statistics for Data Science: The sf package for spatial vector data (spacestats01 3)

Spatial Statistics for Data Science: The sf package for spatial vector data (spacestats01 3)

ISLP: Survival Analysis and Censored Data (islp01 11)

ISLP: Survival Analysis and Censored Data (islp01 11)

R for Data Science: Numbers (r4ds10 13)

R for Data Science: Numbers (r4ds10 13)

R for Data Science: Spreadsheets (r4ds09 21)

R for Data Science: Spreadsheets (r4ds09 21)

EMA: Intro to Instance-level Exploration & Break-down Plots for Additive Attributions (ema01 5 6)

EMA: Intro to Instance-level Exploration & Break-down Plots for Additive Attributions (ema01 5 6)

Mastering Shiny: Why reactivity? (mshiny06 13)

Mastering Shiny: Why reactivity? (mshiny06 13)

Advanced R: Introduction (advr08 1)

Advanced R: Introduction (advr08 1)

Web APIs with R: What are we trying to learn? (wapir01 LO)

Web APIs with R: What are we trying to learn? (wapir01 LO)

Fundamentals of Numerical Computation: Diffusion equations (fnc01 11)

Fundamentals of Numerical Computation: Diffusion equations (fnc01 11)

ISLR: Classification (islr06 4)

ISLR: Classification (islr06 4)