Lecture 9

Course Reflection & Wrap-Up

Byeong-Hak Choe
bchoe@geneseo.edu

SUNY Geneseo

May 6, 2026

✅ Course Reflection & Wrap-Up

📘 What We Worked On This Semester

  • 📈 Regression Models for Inference and Prediction
    • Linear regression and logistic regression
  • ⚖️ Model Evaluation and Validation
    • Understanding why ML methods are important for scalable prediction and generalization
  • 🎯 Regularized Regression for High-Dimensional Data
    • Lasso, ridge, and elastic net regression
  • 🌳 Tree-Based Machine Learning Models
    • Decision trees, random forests, and gradient-boosted trees
  • 🧩 Unsupervised Learning
    • Clustering, PCA, and association rules
  • 🔍 Machine Learning Applications and Project

📝 Student Course Experience (SCE) Survey

Your Feedback Matters

I have made every effort to create a meaningful and supportive learning experience in this course.

Your feedback is extremely valuable and helps improve future versions of the course.

I sincerely encourage you to complete the Student Course Experience (SCE) survey.

✅ Please Take About 10 Minutes Now

🔗 https://go.geneseo.edu/scesurveys

Steps

  1. Log in to the SCE Survey Portal
  2. Click on “Surveys”
  3. Select DANL 320: Big Data Analytics
  4. Complete the evaluation survey

🙌 Thank You

Thank you for being part of DANL 320 this semester.

I really appreciate the effort you put into learning machine learning methods, working with real-world datasets, and thinking about how models can help us make sense of large and complex data.

I hope this course helped you become more confident in using machine learning for big data analytics, including building, evaluating, and interpreting models professionally.

Thank you again for your participation, feedback, and hard work throughout the semester. It has been a pleasure.

— Byeong-Hak