Course Logistics
Contents
Course Logistics¶
Class Meeting Times¶
The course meets twice a week on Mondays and Wednesdays in Ford 342 from 10:50am to 12:05pm. In supporting our course community, students should make every effort to be at our course meetings on time.
Note
For accessibility reasons, we kindly ask that you refrain from wearing any scented products in class.
Attending Lecture¶
We are still in the midst of a global pandemic. In keeping with the Guidelines laid out in Smith’s Culture of Care, if you are ill and/or have any COVID symptoms, please do not come to in-person class. Instead, please log in onto our gather site. The link can be found on our Moodle site and our slack space.
You do not need to email me to ask permission to come to class in gather or in person. However, if you are not able to be in-person for 3 consecutive meetings, then we need to check in.
Similarly, do not come to student hours nor appointments if you are ill and/or have any COVID symptoms. Please use the gather to attend student hours virtually, and a zoom link can be provided for any in-person appointment.
Warning
Do NOT come to in-person class or student hours, if you are ill and/or have any COVID symptoms.
Failure to respect this policy will result in an email to both the class dean and your advisor.
Pivoting Class Meetings¶
If I am unwell and/or experiencing any symptoms of COVID, class will be held on gather. If this happens, I will send a slack message on the #general channel using the @everyone mention. Using @everyone should send an email to your inbox.
If the college remains remote for the whole semester, the course should be able to remain largely remain unchanged. The structure of this course is similar to one that I used in Spring 2021 for Computational Machine Learning. That course was fully online, and students had positive comments on this format.
Communication¶
In addition to our synchronous meetings, our class will make of electronic communication, including our class slack, email, and Moodle messages. These methods of communication represent differing levels of formality and collaboration:
Slack: Our slack site is the primary form of course communication. It allows for us to share where we are stuck with a reading, idea, or assignment, and where we can add helpful hints, request study groups, or share interesting news articles. Slack is much less formal than email, and salutations and signatures are not required. If you need to ask your instructor a question, this is the best place to do it either over a public channel or through direct message. Please make a daily practice of checking slack as the primary form of communication for the course
Email: Email communication is more formal than slack. It should be used in the cases that 1) concern something personal including accommodations forms, 2) require attachments, or 3) involve a number of people (who should be copied on the email). We also will use email to confirm individual appointments. Emails to the instructor should include a salutation and a signature.
Slack Mentions: When I need to communicate with the whole class on a time-sensitive manner, I will use the @everybody or @channel functionality in slack. Please check that your slack settings will notify you either via slack or email. If you are using the email notifications, please be sure that your email does not treat these messages as spam.
Slack Emojis: At times, I will ask you to emoji a message to show that you have read the message. This is a quick way for you to signal that you read it. If there’s something that you have a question about in a “please emoji” message, please use the threading function for that message or send me a direct message on slack.
Note
Please sign up for our slack site, add a profile picture, and introduce yourself with your name and a fun-fact about yourself on the #intros channel. After signing up, please determine how and where you will get notifications from slack.
Please note that on a typical workday, I leave my office just after 4:00pm. This means that emails and slack messages sent after 4:00pm will likely be received on the next business day. Similarly e-communication sent on the weekend will likely not be received until Monday.
Course Resources¶
Machine learning is a rapidly evolving field, and a course focusing on computation (instead of theory) is less common. So, our course will gather together a number of readings and resources from different sources. The below list of course materials are the minimum that I believe that you need to be successful in the course. If you feel that there is something critical missing from this list, please let me know.
Variety of book chapters noted on the detailed course schedule and available at the library
Bound notebook for notes, ideas, and scratch work
Highlighters in at least 2 colors
Pens or pencils in at least 3 colors
Recommended Texts:
Python for Data Analysis by McKinney
Python Machine Learning by Raschka and Mirjalili
Note
Both of our recommended texts are available at the library as E-Books. Please note that if you are viewing the sources online, you may be limiting another person from using it. Instead, you can download sections (or whole books) for a period of time directly from the library.
Instructor Information¶
The instructor for this course is Katherine Kinnaird. My office is room 218 Bass Hall. My email is kkinnaird@smith.edu, but the best way to reach me is on slack.
Student hours¶
My student hours are time blocked in my calendar for you! Please drop by either in person or virtually.
Note
Student hours are:
Wednesdays from 3pm to 4pm
Thursdays from 11am to noon
By appointment
Below is an incomplete list of great reasons to hangout in gather before or after class or to make an appointment:
You haven’t had the chance to chat with me yet
You want to see what my home office (ie. my basement) looks like without having to split your focus with learning
You have a question on a reading, assignment, or activity
You heard that that my office mascot is a sheep
You want to share about the course, your time at Smith, or about yourself
You read something about machine learning, computer science, statistics, or math that you have questions about
You are thinking about what you want to do after Smith
Appointments¶
You are welcome and encouraged to make individual appointments with me. To make an appointment, please check my appointment calendar for appointment slots that are set aside each week.
Note
To book an appointment with me, go to my appointment calendar