logo

CS456: Machine Learning (2/2019)


Meeting: Tues-Fri, 11.00-12.30 @ CSB202


Instructor: Jakramate Bootkrajang
Office : 15.30-16.30 Tuesday-Friday @ CSB 107
Email: jakramate.b@cmu.ac.th
Announcements
Greeting!!
ให้นักศึกษาตั้งทีมแล้วเข้าทดลองส่งคำตอบได้ที่ [link]
Dart score prediction is now on Kaggle [link]
Hackathon [link]
Assignment 1 is announced
Assignment 2 is announced
DA decision boundary [colab]
Linear regression code [colab]
Assignment 3 is announced
Midterm scores announced [link]
Syllabus
DateLectureDateLectureHW
17 Dec Admin 20 Dec Introduction to ML [link]
24 Dec Math refresher 27 Dec Regression
31 Dec New year 3 Jan New year
7 Jan Linear Least Square [colab] 10 Jan Classification Dart score prediction
13 Jan SVM 17 Jan SVM + Kernel
20 Jan Logistic Regression 24 Jan Discriminant Analysis [colab] [pdf] (due 28 Jan)
27 Jan Neural Networks 31 Jan Backpropagation Backprop by example
4 Feb Deep learning (1) 7 Feb Deep learning (2)
11 Feb Classifier evaluations 15 Feb Exam preparation CNN homework
18 FebMidterm examination 15.30-18.30
DateLectureDateLabHW
25 Feb Clustering and k-means 28 Feb Mixture model[slides]
3 Mar Cluster evaluation 6 Mar Dimensionality reduction and PCA
10 Mar Dimensionality reduction and PCA 13 Mar Independent Component Analysis [reading]
17 Mar Bias/Variance Trade-off 20 Mar Regularisations
24 Mar Reinforcement learning + Markov Process 27 Mar Markov Decision Process + Value-iteration
31 Mar Q-learning 3 Apr Wrap-up
6 Apr TBD 10 Apr TBD
14 Apr Thai New year 17 Apr Thai New year
23 AprFinal examination (regular exam) 15.30-18.30

Assigments (via Kaggle competition platform)
Assignment 0: System testing (due 20 Dec.) Competition link
Assignment 1: New york taxi fare prediction (subsampling version) (due 2 Feb) Competition link
Assignment 2: (SVM & LR written assignment) [pdf] (due 28 Jan)
Assignment 3: Flower Classification with TPUs (due 17 Mar) Competition link
หมายเหตุ การบ้านนี้จำเป็นต้องใช้การประมวลผลบน GPU หรือ TPU นักศึกษาอาจเริ่มต้นจาก notebook แนะนำนี้ ซึ่งมีโควต้าในการใช้งาน TPU ของ Kaggle จำนวน 30 ชั่วโมงต่อเดือน [link]

Grading
Midterm: 35%
Final 35%
Assignments: 30%

Useful resources
Book
Machine learning by Tom Mitchell
Pattern Recognition and Machine Learning by Chris Bishop
Foundation of Machine learning by Mehryar Mohri et. al.
Kernel Methods for Pattern Analysis by John Shawe-Taylor et al.
Online Materials
Scikit-learn
Anaconda
Julia language quick introduction
Back to Top