Learning Labs Pro

Founder of Business Science and general business & finance guru, He has worked with many clients from Fortune 500 to high-octane startups! Matt loves educating data scientists on how to apply powerful tools within their organization to yield ROI. Matt doesn’t rest until he gets results (literally, he doesn’t sleep so don’t be suprised if he responds to your email at 4AM)!

Here’s what you’ll get:

Welcome to Learning Labs PRO!

• Learning Labs PRO! (0:52)
• Thank You For Joining LL PRO – Here’s The Dime Tour!
• Join Our Slack Channel

R in Production | MLOps Series

• Lab 41: Forecasting at Scale with MetaFlow + Modeltime + AWS (97:21)
• Lab 40: Docker for Data Science (91:37)
• Lab 39: H2O & MLFlow for Bankruptcy Prediction API (88:47)

SPECIAL: Forecasting with Modeltime!

• Lab 38: Time Series Forecasting with Modeltime (85:29)

Python + R Series

• Lab 37: NLP & PDF Text Extraction (spaCy) (100:37)
• Lab 36: Tensorflow Multivariate Forecasting (Energy, LSTM) (108:17)
• Lab 35: TensorFlow for Finance & Gold Price Forecaster App (Time Series, LSTM) (119:27)
• Lab 34: Advanced Customer Segmentation & Market Basket App (E-Commerce) (107:21)
• Lab 33: Employee Segmentation w/ Scikit-Learn (HR Analytics) (88:08)

Shiny API Series

• Lab 32: Text Mining Tweets with Twitter & Tidytext (91:07)
• Lab 31: Forecasting Google Analytics with Facebook Prophet & Shiny (79:26)
• Lab 30: Shiny Finance with Tidyquant (Excel in R) (88:54)
• Lab 29: Shiny Crude Oil Forecast (Multivariate ARIMA) App with Fable & Quandl API (83:13)
• Lab 28: Shiny Real Estate App with Zillow API (72:50)

Marketing Analytics Series

• Lab 27: Google Trends Automation with Shiny (66:52)
• Lab 26: Machine Learning for Customer Journey (96:38)
• Lab 25: Marketing Multi-Channel Attribution with ChannelAttribution (96:08)
• Lab 24: A/B Testing for Website Optimization with Infer & Google Optimize (90:59)
• 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)

Databases – SQL

• Lab 23: Google Analytics & BigQuery (SQL) – Conversion Funnel Analysis (85:04)
• Lab 22: SQL for Time Series – Stocks & Fannie Mae Mortgage Delinquency Analysis (90:16)
• Lab 21: SQL for Data Science – Home Loans with SQL, R, & dplyr (92:06)

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)

Data Collection

• Lab 8: Web Scraping – Build A Strategic Database With Product Data (70:07)

Domain: Finance

• Lab 9: Finance with R – Performance Analysis & Portfolio Optimization with tidyquant (77:35)

Advanced Functional Programming

• Lab 12: How I Built This – R Package Anomalize using Tidy Eval & Rlang (74:50)

Machine Learning – Beginning of Coded Labs

• Lab 5: Hands-On Coding with the NEW parsnip package (75:54)
• Lab 4: H2O AutoML – Erin LeDell Guest Appearance! (87:15)

Free / No-Code Labs (Before we transitioned to FULL CODE Labs)

• [IMPORTANT] Labs 1-6 were made before LL PRO existed.
• Lab 6: Communicating Machine Learning with the rmarkdown package (71:38)
• Lab 2: R In Production: Building Production-Quality Apps with Shiny (55:32)
• Lab 1: How to Learn R Fast! (56:35)