2025 spring

(2 Div)

Instruction

Course Staff
Time & Location
  • Tue./Wed. 09:00 - 10:45, #608, College of Engineering #6
Office Hours
  • Tue. 13:00 - 15:00
Textbook
  • Primary
    • [Ge23] Aurélien Géron. 2023. Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems, 3rd Ed. O`Reilly
  • Secondary
    • [Fo23] David Foster. 2023. Generative Deep Learning: Teaching Machines to Paint, Write, Compose and Play, 2nd Ed. O`Reilly
    • [Ow22] Louis Owen. 2022. Hyperparameter Tuning with Python: Boost your machine learning model’s performance via hyperparameter tuning. Packt.
    • [Br20] Jason Brownlee. 2020. Data Preparation for Machine Learning, 1.1 Ed. Machine Learning Mastery
    • [Br21] Jason Brownlee. 2021. Imbalanced Classification with Python, 1.3 Ed. Machine Learning Mastery
Prerequisite
  • Python Programming, Data Analysis Programming
    • All materials were prepared assuming students were proficient in Python programming and familiar with Numpy and Pandas.
Grading Policy
Data Collection (10%)
  • Collect sensor data for human activity recognition
Individual ML Competitions via Kaggle (80%)
  • Round 0 - Being Familiar with Kaggle (5%)
  • Round 1 - TBD (9%)
  • Round 2 - TBD (9%)
  • Round 3 - TBD (9%)
  • Special Round - TBD (15%)
  • Round 4 - TBD (9%)
  • Round 5 - TBD (9%)
  • Final Round - Human Activity Recognition (15%)
Attendance (10%)
  • 1% of credit is deducted for each absence
  • 3-Lateness = 1-Absence
  • 11-Absence = F grade

Schedule

Week 01
March 04: Overview & Logistics
March 05: Machine Learning Landscape
Week 02
March 11: Machine Learning Pipeline
  • Lecture
  • Reference
    • [Ge23] Chap. 2
    • D. Sculley et al. 2015. Hidden technical debt in Machine learning systems. In Proceedings of the 28th International Conference on Neural Information Processing Systems - Volume 2 (NIPS'15).
    • Soowon Kang et al. 2023. K-EmoPhone: A Mobile and Wearable Dataset with In-Situ Emotion, Stress, and Attention Labels. Sci Data 10, 351 (2023).
March 12: End-to-End Practice for Machine Learning Pipeline
  • Practice
  • Reference
    • [Ge23] Chap. 3
  • (Announce) Individual ML Competition Round 0: Getting Familiar w/ Kaggle
    • Due: March 18
Week 03
March 18: Linear Model
March 19: Linear Model - Practice
  • Practice
  • Reference
    • [Ge23] Chap. 4
  • (Announce) Individual ML Competition Round 1: Telemarketing
    • Due: March 31
Week 04
March 25: Performance Measures
March 26: Cross-Validation
Week 05
April 01: Support Vector Machine
April 02: Decision Tree
  • Lecture
  • Practice
  • Reference
    • [Ge23] Chap. 6
  • (Announce) Individual ML Competition Round 2
    • Due: April 14
Week 06
April 08: Ensemble Learning #1: Random Forest
April 09: Ensemble Learning #2: Gradient Boosting
Week 07
April 15: Imbalanced Classification
April 16: Feature Extraction
  • Lecture
  • Practice
  • Reference
    • Andreas Bulling et al. 2014. A tutorial on human activity recognition using body-worn inertial sensors. ACM Comput. Surv. 46, 3, Article 33.
    • Soujanya Poria et al. 2017. A review of affective computing: From unimodal analysis to multimodal fusion. Information Fusion, 37, 98–125.
  • (Announce) Individual ML Competition Midterm Round
    • Due: April 28
Week 08
April 22: Feature Selection
April 23: Focus on Midterm Exam
  • No Class
Week 09
April 29: Unsupervised Learning - Dimensionality Reduction
April 30: Unsupervised Learning - Clustering
  • Lecture
  • Practice
  • References
    • [Ge23] Chap. 9
  • (Announce) Individual ML Competition Round 3
    • Due: May 12
Week 10
May 06: Substitution Holiday for Children's Day
  • No Class
May 07: Hyper-parameter Tuning #1
  • Lecture
  • Practice
  • Reference
    • [Ow22] Chap. 2, 3, 4, 7, 8
    • Tong Yu and Hong Zhu. 2000. Hyper-Parameter Optimization: A Review of Algorithms and Applications
Week 11
May 13: Hyper-parameter Tuning #2
  • Lecture
  • Practice
  • Reference
    • [Ow22] Chap. 5, 6, 9, 10
    • Tong Yu and Hong Zhu. 2000. Hyper-Parameter Optimization: A Review of Algorithms and Applications
May 14: Deep Learning - Artificial Neural Network
  • Lecture
  • Practice
  • References
    • [Ge23] Chap. 10
  • (Announce) Individual ML Competition Round 4
    • Due: May 26
Week 12
May 20: Deep Learning - Deep Neural Network
  • Lecture
  • Practice
  • References
    • [Ge23] Chap. 11
  • (Announce) Data Collection Assignment: Sensor Data Collection
    • Due: June 03
May 21: Deep Learning - Convolution Neural Network
Week 13
May 27: Deep Learning - Recurrent Neural Network
May 28: Generative Models - Autoencoder
  • Lecture
  • Practice
  • References
    • [Ge23] Chap. 17
  • (Announce) Individual ML Competition Round 5
    • Due: June 09
Week 14
June 03: Substitution Holiday for Presidential Election
  • No class
June 04: Generative Models - Variational Autoencoder & Autoregressive Models
Week 15
June 10: Generative Models - Generative Adversarial Network
June 11: Generative Models - Diffusion Model
  • Lecture
  • References
    • [Fo23] Chap. 8
  • (Announce) Individual ML Competition Final Round
    • Due: June 22
Week 16
June 17: Focus on Final Assigment
  • No Class
June 23: Final Remark