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List of videos from conferences related to R and Data
- Alternative Data in Institutional Investing: Common Problems Solved with R
- But When You Call Me Bayesian, I Know I’m Not the Only One
- Dashboarding with Shiny
- Data Analysis with Julia & R
- DataFrames: The Good, Bad, and Ugly
- David & Goliath
- Engagement & Reality
- Hiring by Human / Machine Learing
- htmlwidgets
- Interactive Ebola Plots in Shiny
- Leveraging RHadoop in Analyzing Multiple Myeloma Patient Timelines
- Making R Go Faster and Bigger
- No One Knows What It's Like to Be the Bad Man: The Development Process for the Caret Package
- Practical Principles for Scalable Statistical Analysis
- R for Every Survey Analysis
- Reproducible Analysis in Production: Lessons from Etsy
- Reproducible Data Analysis with Revolution R Open
- Software Architecture and Predictive Models in R
- Storytelling with Data Visualizations
- The Data Perspective
- Visualizing Livability in NYC
- A Statistician Walks into a Tech Company: R at a Rapidly Scaling Healthcare Startup
- An Economic Research Platform using R, Semantic Technologies, and Lambda Architecture
- Analyzing NYC Transit Data
- Behavior Quantified
- Broom: Converting Statistical Models to Tidy Data Frames
- Building Scalable Prediction Services in R
- Complementary Recommendations at eBay: Tackling the Challenges of a Semi-Unstructured
- Data Science Challenges in Personal Program Analysis
- Gadgets, Addins, and HTML Templates
- High-Performance Python
- Improving Data Interoperability for Python and R
- Iterating Over Statistical Models: NCAA Tournament Edition
- Notebooks (and more) with R Markdown
- One Algorithm to Rule Them All: How to Automate Statistical Computation
- R for Everything
- R Packages for Time-Varying Networks and Extremal Dependence
- RCloud - Collaborative Environment for Visualization and Big Data Analytics
- Reflection on the Data Science Profession
- Scaling Data Science at Airbnb
- Testing Your Data and Code in R
- The Feels
- The Political Impact of Social Penumbras
- Thinking Small About Big Data
- Using R at NYT Graphics
- What do Authors, Neurons, and Enterprise Suppliers Have in Common?
- What We Learned Building an R-Python Hybrid Predictive Analytics Pipeline
- An R Cloud Computing Lifeline: The Missing Manual for Running R on Amazon Cloud
- Better Packages through Peer Review: Lessons from rOpenSci
- Building a Predictive Early Intervention System to Prevent Adverse Police Incidents
- Don't Let Lawyers Ruin Your Analytics
- Enabling reproducibility at scale with R and Pachyderm
- Experience R in the Cloud: Empower Insurance Operations from Insights to Action
- Fine Grained Visual Category Recognition and Perceptual Embedding
- From Agreeing to Marching to Organizing: OSS Needs You
- Fun with R
- Harnessing the Power of JavaScript for Data Science
- How R Helps Airbnb Make the Most of Its Data
- Live Tweeting: Qualitative and Quantitative Advice
- Publication Hacking: How We Answered a Research Question and Wrote a Manuscript in Only Two Days
- R in Financial Services: Challenges and Opportunities
- R Makes the World Go ‘Round: Data Driven Decision Making at JetBlue
- R: From Backend to Production
- RStudio Tips and Tricks
- So You Want to be a Data Scientist?
- Text Mining, the Tidy Way
- The Humble Programmer Data Scientist: Essence and Accident in Software Engineering Data Science
- The Unreasonable Effectiveness of Empathy - The killer skill needed for a successful technical career
- Theoretical Statistics is the Theory of Applied Statistics: How to Think About What We Do
- Things about the Future and the Future of Things
- threejs: less cruft, more awesome!
- Towards Interoperable Data Frames
- Using Human Mobility Data to Assess Public Circulation Health
- We R What We Ask: The Landscape of R Users on Stack Overflow
- No-Bullshit Data Science
- Detecting Fraud at 1 Million Transactions per Second
- Risk Fast and Slow
- Reproducible Finance with R: A Global ETF Map
- Markov-Switching GARCH Models in R: The MSGARCH Package
- Scenario Analysis of Risk Parity using RcppParallel
- Efficient, Consistent and Flexible Credit Default Simulation + Machine Learning and the Analysis of Consumer Lending
- MLEMVD: An R Package for Maximum Likelihood Estimation of Multivariate Diffusion Models
- Forecasting Performance of Markov-Switching GARCH Models: A Large-Scale Empirical Study
- Revealing High-Frequency Trading Provisions of Liquidity with Visualization in R
- Equity Factor Portfolio Case Study
- R package mcrp: Multiple criteria risk contribution optimization
- A Bayesian Multivariate Functional Dynamic Linear Model
- Syberia: A development framework for R
- yuimaGUI: A graphical user interface for the yuima package
- Lightning Talks I (Day 1)
- Lightning Talks II (Day 1)
- Lightning Talks III (Day 1)
- Lightning Talks I (Day 2)
- Closing Sessions: Matt Dancho (tidyquant), Leonardo Silvestri (ztsdb)
- Closing Session: Bryon Lewis - Project and Conquer
- Efficient R programming
- Create interactive maps in seconds with R and Leaflet
- Spark and R with sparklyr Part 1 Part 2
- Just enough Scala for Spark Part 1 Part 2
- Using R and Spark to analyze data on Amazon S3 - Edgar Ruiz (RStudio)
- Machine learning in R - Jared Lander (Lander Analytics) WORKSHOP Part 1 Part 2 Part 3 Part 4
- Teaching data science to new useRs
- 20 years of CRAN
- Structural Equation Modeling: models, software and stories
- Parallel Computation in R: What We Want, and How We (Might) Get It
- R tools for the analysis of complex heterogeneous data
- Developing and deploying large scale Shiny applications for non-life insurance 👍
- Exploring and presenting maps with tmap
- Package ggiraph: a ggplot2 Extension for Interactive Graphics
- Spatial data in R: simple features and future perspectives
- mapedit: interactive manipulation of spatial objects
- Visual funnel plot inference for meta-analysis
- Implementing R in old economy companies: From proof-of-concept to production
- Interacting with databases from Shiny
- Statistics in Action with R: an educative platform
- Data Carpentry: Teaching Reproducible Data Driven Discovery
- Using R in a regulatory environment: FDA experiences
- A Benchmark of Open Source Tools for Machine Learning from R
- Too good for your own good: Shiny prototypes out of control
- Beyond Prototyping: Best practices for R in critical enterprise environments
- Implementing Predictive Analytics projects in corporate environments
- shiny.collections: Google Docs-like live collaboration in Shiny
- A first-year undergraduate data science course
- ShinyProxy
- Modeling Food Policy Decision Analysis with an Interactive Bayesian Network in Shiny
- Statistics and R in Forensic Genetics
- RQGIS: integrating R with QGIS for innovative geocomputing
- Interfacing Google's spherical geometry library (S2) for spatial data in R
- Analysis of German Fuel Prices with R
- Scraping data with rvest and purrr
- Show me the errors you didn't look for
- Clouds, Containers and R, towards a global hub for reproducible and collaborative data science
- Automatically archiving reproducible studies with Docker
- codebookr: Codebooks in R
- When is an Outlier an Outlier? The O3 plot
- Distributional Trees and Forests
- Two-sample testing in high dimensions
- Bayesian analysis of generalized linear mixed models with JAGS
- A Tidy Data Model for Natural Language Processing
- Text mining, the tidy way
- Untidy Text Analysis Using R with quanteda)
- Neural Embeddings and NLP with R and Spark
- ReinforcementLearning: A package for replicating human behavior in R
- Deep Learning for Natural Language Processing in R
- R4ML: A Scalable R for Machine Learning
- jug: Building Web APIs for R
- R Package glmm: Likelihood-Based Inference for Generalized Linear Mixed Models
- countreg: Tools for count data regression
- MCMC Output Analysis Using R package mcmcse
- Estimating the Parameters of a Continuous-Time Markov Chain from Discrete-Time Data with ctmcd
- EpiModel: An R Package for Mathematical Modeling of Infectious Disease over Networks
- Social contact data in endemic-epidemic models and probabilistic forecasting with surveillance
- brms: Bayesian Multilevel Models using Stan
- Markov-Switching GARCH Models in R: The MSGARCH package
- Transformation Forests
- Actuarial and statistical aspects of reinsurance in R
- Interactive bullwhip effect exploration using SCperf and Shiny
- Ensemble packages with user friendly interface: an added value for the R community
- Taking Advantage of the Byte Code Compiler
- Can you keep a secret?
- We R What We Ask: The Landscape of R Users on Stack Overflow
- How we built a Shiny App for 700 users?
- bradio: Add data music widgets to your business intelligence dashboards
- Navigating the R package universe
- A quasi-experiment for the influence of the user interface on the acceptance of R
- data.table for beginners I
- data.table for beginners II
- Geospatial visualization using R I
- Geospatial visualization using R II
- Spatial data in R: new directions I
- Spatial data in R: new directions II
- Efficient R Programming I
- Efficient R Programming II
- Solving iteration problems with purrr I
- Solving iteration problems with purrr II
- Sports Analytics with R I
- Sports Analytics with R II
- Rcpp: From Simple Examples to Machine Learning I
- Rcpp: From Simple Examples to Machine Learning II
- Introduction to parallel computing with R I
- Introduction to parallel computing with R II
- Data Carpentry: Open and Reproducible Research with R I
- Data Carpentry: Open and Reproducible Research with R II
- Introduction to optimal changepoint detection algorithms I
- Introduction to optimal changepoint detection algorithms II
- Connecting R to the Machine Learning Platform OpenML I
- Connecting R to the Machine Learning Platform OpenML II
- Introduction to Bayesian inference with JAGS I
- Introduction to Bayesian inference with JAGS II
- Introduction to Natural Language Processing with R I
- Introduction to Natural Language Processing with R II
- Modelling the environment in R: from small-scale to global applications I
- Modelling the environment in R: from small-scale to global applications II
- Dose-response analysis using R I
- Dose-response analysis using R II
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