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Explainable Machine Learning
Lab 20 - Explaining Machine Learning for Customer Churn (79:03)
Network Analysis
Lab 19 - Using Customer Credit Card History to Cluster with Network Analysis (83:09)
Anomaly Detection
Lab 18 - Time Series Anomaly Detection - anomalize (87:15)
Lab 17 - Anomaly Detection with H2O Machine Learning (90:34)
Optimization & Simulation
Lab 16: R Optimization Toolchain - Part 2 - Stock Portfolio & Nonlinear Programming with ROI (88:09)
Lab 15: R Optimization Toolchain - Part 1 - Product Mix & Linear Programming with ompr (80:35)
Big Data
Lab 13: Wrangling 4.6M Rows (375 MB) of Financial Data with data.table (78:36)
Time Series
Lab 7: 5 Strategies to Improve Business Forecasting by 50% (or more) (89:02)
Production: Shiny & Plumber
Lab 10: Building API's with Plumber & Postman (80:18)
Lab 2: R In Production: Building Production-Quality Apps with Shiny (55:32)
Data Collection
Lab 8: Web Scraping - Build A Strategic Database With Product Data (70:07)
Machine Learning
Lab 5: Hands-On Coding with the NEW parsnip package (75:54)
Lab 4: H2O AutoML - Erin LeDell Guest Appearance! (87:15)
Domain: Finance
Lab 9: Finance with R - Performance Analysis & Portfolio Optimization with tidyquant (77:35)
Domain: Marketing
Lab 14: Customer Churn Survival Analysis w/ correlationfunnel, parsnip, & H2O (88:30)
Lab 11: Market Basket Analysis & Recommendation Systems w/ recommenderlab (78:35)
Lab 3: Marketing Analytics Case Study - Excel to R (77:54)
Reporting & RMarkdown
Lab 6: Communicating Machine Learning with the rmarkdown package (71:38)
Learning R
Lab 1: How to Learn R Fast! (56:35)
Advanced Functional Programming
Lab 12: How I Built This - R Package Anomalize using Tidy Eval & Rlang (74:50)
Lab 12: How I Built This - R Package Anomalize using Tidy Eval & Rlang
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