Introduction to Machine Learning
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No nanoquiz or labs this week.
CROSS REGISTERED STUDENTS: email email@example.com for section assignments, as Stellar may take a while to update.
The Fall 18 is almost here! Here is some basic information about 6.036.
The following message was sent to all pre-registered students. Please read it carefully all the way through.
Your first 6.036 “class” will be a lab on September 5 or September 7. It is important to attend a lab meeting in the first week.
The first lecture will be on Tuesday September 11, 9:30-11:00 in 32-123. We are expecting more people than can fit in that room, so there will be a simulcast in 32-155. Each student will be required to attend one lab section for 1.5 hours each week. These meetings will be in 34-501. There are 6 lab times: Wednesdays at 11am and 1pm and Fridays at 9:30am, 11am, 1pm, and 2:30pm.
The Registrar will make an initial assignment to sections. These assignments will appear on Stellar (https://stellar.mit.edu/). We cannot influence these assignments, so please don’t email us requesting a section. For the first week or so of the term, you will be able to make section changes on Stellar, subject to the capacity limits of the room. If you are not assigned a section, please pick one on Stellar. If you are cross-registering, please make sure that you have an MIT email so that you can use Stellar.
You may not attend a section other than your assigned one. At the beginning of each section meeting, there will be a short 15-min quiz (administered on-line). You will not be able to access the quiz if you are not assigned to that section.
Please bring a laptop to your section meeting; if you do not have a laptop we have some available for loan, but it will be better to have a computer you are familiar with, if possible. All other class assignments will be done on-line.
You cannot understand machine learning without understanding vectors, dot products, matrices and partial derivatives well. You should feel comfortable with roughly the first 6 weeks of this 18.02 material. You should be able to do practice exams 1 and 2 (it’s fine if you need to use some reference material or look things up) from 18.02. Some additional exposure to linear algebra (linear independence) and probability (conditional probability, expectations) is helpful but can be picked up along the way. We also expect you to feel very comfortable with writing and, importantly, debugging Python programs.