Repo for Practicing R based on R Documentation, and Machine Learning for Business Analytics
Disclaimer: This repo is self-studied. All guidelines for projects are self-generated and may not be comprehensive of MLBA's spirit.
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12/15/24 Init
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12/24/24 Project Guidelines
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1/14/25 Scope expanded to include GTx Micromasters classes
"Course" ORDER:
- C1: Introduction
- C2: Overview of the Machine Learning Process
- C3: Data Visualization
- C4: Dimension Reduction
- C5: Evaluating Predictive Performance
- C21: Text Mining
- C6: Multiple Linear Regression
- C7: k-Nearest Neighbors
- C8: The Naive Bayes Classifier
- C9: Classification and Regression Trees
- C10: Logistic Regression
- C11: Neural Nets
- C12: Discriminant Analysis
- C13: Generating, Comparing, and Combining Multiple Models
- C14: Interventions: Experiments, Uplift Models, and Reinforcement Learning
- C15: Association Rules and Collaborative Filtering
- C16: Cluster Analysis
- C17: Handling Time Series
- C18: Regression‐Based Forecasting< 52E5 /li>
- C19: Smoothing and Deep Learning Methods for Forecasting
- C20: Social Network Analytics
- C22: Responsible Data Science
- C23: Cases