Beware: exercises on monday 25. august.
Dear all,
We hope you are enjoying a relaxing summer break, and if you are in Denmark, appreciating the charm of a classic Danish summer. We look forward to welcoming you to next semester’s course “Introduction Machine Learning”, where we will cover a range of key topics of machine learning.
This page contains important information to help you get off to a smooth start, so please read it carefully and well in advance. We aim to give you enough time to prepare, so you start the semester with a refreshed mind and the preparation you need.
The first lecture and exercises start in the week of Monday 25. August.
Beware: exercises on monday 25. august.
We do not expect that you understand all material prior to attending lectures and exercises. However, we strongly recommend that you have prepared for both before attending while skipping the parts that you do not understand. This ensures efficient learning and makes better use of resources, including your time and TA assistance.
Exercises are usually related to and numbered according to the lecture. Hence the exercises “W1” is intended for the exercises after the lecture 1. This should give you time to read the material (again) and attempt to make some of the exercises.
This course builds on mathematical concepts typically taught in high school. We recognize that it may have been a while since you last worked with such material. It introduces mathematical modeling, which may differ from your past experience with mathematics.These concepts will be used actively from the first week. We have assembled a set of resources that we strongly encourage you to review before the semester starts. If you need help after going through the material, we can arrange an online session outside of the scheduled lectures once the semester begins.
We suggest that you:
Read and complete the “Prerequisite Material” under “Course Guidelines” tab on iml.itu.dk , well in advance of the semester start. This page includes important background information and exercises, such as reviewing vectors and solving linear equations (e.g., two equations with two unknowns), which may require some time to work through.
Allocate time in your calendar. As you will likely be taking multiple courses this semester, it is easy to underestimate the importance of balancing your time across them. For Introduction to Machine Learning (IML), you are expected to dedicate 11.8 hours per week (corresponding to 7.5 ECTS) exclusively to this course. Unlike some other courses, IML will require you to consistently spend the expected number of hours each week. We therefore strongly recommend that you schedule these hours in your calendar and coordinate with your studygroup (if you have one) at the beginning of the semester. It is important that you let us know if you consistently spend more time during the semester.
We will be using python for the exercises. While it is not a prerequisite to be proficient in python programming, we do suggest you familiarize yourself with the language prior to starting the semester to free-up time for other things during the semester.
The preparatory exercises “Course Guidelines” tab on iml.itu.dk are intended to help you setup a functioning python environment and get acquainted with Python.
The course assumes a rather specific python setup, that we can support please follow the installation instructions carefully and avoid being too creative with your installation.
Dan