6.036 Introduction to Machine Learning (Spring 2017)

Machine learning methods are commonly used across engineering and sciences, from computer systems to physics. Moreover, commercial sites such as search engines, recommender systems (e.g., Netflix, Amazon), advertisers, and financial institutions employ machine learning algorithms for content recommendation, predicting customer behavior, compliance, or risk. As a discipline, machine learning tries to design and understand computer programs that learn from experience for the purpose of prediction or control. In this course, you will learn about principles and algorithms for turning training data into effective automated predictions. We will cover concepts such as representation, over-fitting, regularization, and generalization; topics such as clustering, classification, recommender problems, probabilistic modeling, reinforcement learning; and methods such as on-line algorithms, support vector machines, neural networks/deep learning, hidden Markov models, and Bayesian networks.

(Students in 6.862, the graduate version, should also check http://courses.csail.mit.edu/6.862/)

Teaching staff (6036-staff@lists.csail.mit.edu): (please read this page carefully before contacting the staff)

Lectures: (tentative schedule)


Exams (60% of grade):

  1. Midterm on Thursday March 23, closed book, 1.5h, in-class, 20% of grade. If you have a conflict with the exam time, please notify us of your midterm conflict at least two weeks before the exam. The conflict exam (with permission only) will be the next day (Friday, March 24). In exceptional cases, the weight of the midterm can be shifted to the final exam.

  2. Final exam on Thursday, May 25 from 9:00 to 12:00 noon in Track, exam is closed book, 3h, 40% of grade. Any conflicts with the final exam time are handled by the registrar's office.

Assignments (40% of grade in total, schedule):

All the assignments will be made available and require submission through 6.036 Stellar page
  1. 5 regular homework assignments (10% of the grade in total).

  2. Three projects, each worth 10% of the grade, involving programming in python.

Discussion forum

We will subscribe all the registered students (students in 6.036 and 6.862) to the course Piazza forum. This is the primary forum for questions pertaining to the course material, logistics, assignments, or exams. Please DO NOT send such questions to individual staff members or to the staff email list. Only queries pertaining to exceptions should be submitted to the staff list (never to individual staff members)