An introduction to neural networks from biological and machine learning perspectives. Focuses on neural networks for classification and regression involving large image and text datasets. Topics include fundamental design principles; supervised and unsupervised learning; fully connected and convolutional networks; transfer learning. Students obtain hands-on experience implementing and analyzing the neural networks covered each week in regular projects that explore different application areas.
|Times & Locations||
TR 9:30 - 10:45 am
|Instructor||Oliver W. Layton
Office: Davis 115 Email: firstname.lastname@example.org Office hours: Here are my weekly office hours. Please reach out — I would like to get to know you!
T (Office) 2:30pm-4:00pm
W (Zoom* or Office) 11:00am-1:00pm
R (Office) 12:00pm-2:00pm
*Zoom is the default, W office hours may be in-person some weeks. Please assume it is Zoom unless I let you know otherwise. Zoom link and sign-in sheet is available on Google Classroom.
|Masking||Health and wellness are crucial to learn most effectively and produce the best quality work in this class. To serve these goals and minimize illness-related "downtime" for as many people as possible masks will be required in class. I will distribute masks on the first day of class.|
There will be regular opportunities for you to practice what you have learned and to demonstrate your accomplishments.
The course grade will be determined as follows:
Work done in teams of two.
Projects are generally due on Thursdays (except for the first few weeks).
Draft and final due dates
There are two types of project due dates:
Between draft and final submissions, code is turned in weekly. The weekly deadline is Thursday at 11:59pm EST.
The draft and final submission schedule depends on the project length:
Submitting a project
Draft and final submissions should be submitted as a ZIP file to Google Classroom to the posted Project assignment there. Only one team member should do this.
The zip file should be named based on the submitting team member's Colby username (e.g.
|Project Late Policy||
Projects are an important part of the learning experience in this course. I do not want you to get behind with the project workload. To encourage this, projects later than 1 week past the due date will not be accepted.
Late projects submitted within this 1 week grace period will not be eligible for extension credit and will be capped at a maximum of 26/30.
Please contact me immediately in the event of illness and other unforeseen circumstances, we will work out accommodations.
Group work is an important component of the learning experience in this course. You and your team member should feel empowered to contribute with your maximum potential and creativity so that everyone can learn effectively. This requires open communication and respect for each other's contributions and time.
To encourage everyone to reflect on this throughout the course, everyone will fill out a short form to evaluate the team experience when you submit each project. I understand that your workload outside of this course fluctuates during some weeks of the semester. The key is open communication and accountability with your team so that the workload can be distributed equitably and fairly. I expect you to reach out to your team member and me if this is not the case.
The team participation form is only filled out when turning in final submissions (not drafts).
There will be a cumulative final exam on Fri Dec 16 1:30pm. Its format will be announced later.
It should go without saying that you should back up any files related to this course. If the code you submit to us is somehow lost (through your fault or our fault), I must be able to get another copy from you. I suggest keeping your code on a cloud storage provider (shared with your team member) Google Drive, Dropbox, or Microsoft OneDrive. That way, you have a backup stored in the cloud.
A private GitHub repository (with your team member set as a collaborator) is another good backup option.
If you use filer, be aware that off campus you need VPN access, which could be unreliable.
Also, you must store data in either your
Here are the expectations for collaboration on projects in a team-based environment:
|Collaboration, Academic honesty||
Computer science, both academically and professionally, is a collaborative discipline. In any collaboration, however, all parties are expected to make their own contributions and to generously credit the contributions of others. In our class, therefore, collaboration on assignments is encouraged, but you as an individual are responsible for understanding all the material in the assignment and doing your own work. The following rules are intended to help you get the most out of your education and to clarify the line between honest and dishonest work:
I do use automated plagiarism detection software, so please be sure to abide by these, rather minimal, rules. Reports of academic dishonesty are handled by an academic review board and a finding of academic dishonesty may result in significant sanctions. For more details on Colby's Academic Integrity policies and procedures, see colby.edu/academicintegrity.
|The Colby Affirmation||
Colby College is a community dedicated to learning and committed to the growth and well-being of all its members.
As a community devoted to intellectual growth, we value academic integrity. We agree to take ownership of our academic work, to submit only work that is our own, to fully acknowledge the research and ideas of others in our work, and to abide by the instructions and regulations governing academic work established by the faculty.
As a community built on respect for ourselves, each other, and our physical environment, we recognize the diversity of people who have gathered here and that genuine inclusivity requires active, honest, and compassionate engagement with one another. We agree to respect each other, to honor community expectations, and to comply with College policies.
As a member of this community, I pledge to hold myself and others accountable to these values. More ...
I am available to discuss academic accommodations that any student with a documented disability may require. Please note that you’ll need to provide a letter from the Dean of Studies Office documenting your approved accommodations. Please meet with me to make a request for accommodations at the beginning of the semester--and at a minimum two weeks before any key due dates--so that we can work together with the College to make the appropriate arrangements for you.
(Title IX Statement)
Colby College prohibits and will not tolerate sexual misconduct or gender-based discrimination of any kind. Colby is legally obligated to investigate sexual misconduct (including, but not limited to, sexual assault and sexual harassment) and other specific forms of behavior that violate federal and state laws (Title IX and Title VII, and the Maine Human Rights Act). Such behavior also requires the College to fulfill certain obligations under two other federal laws, the Violence Against Women Act (VAWA) and the Jeanne Clery Disclosure of Campus Security Policy and Campus Statistics Act (Clery Act).
To learn more about what constitutes sexual misconduct or to report an incident, see: https://www.colby.edu/sexualviolence/.
If you wish to speak confidentially about an incident of sexual misconduct, you may contact:
Students should be aware that faculty members are considered "responsible employees"; as such, if you disclose an incident of sexual misconduct to a faculty member, they have an obligation to report it to Colby's Title IX Coordinator. "Disclosure" may include communication in-person, via email/phone/text, or through class assignments.
|Observance of Religious holidays||
Colby College supports the religious practices of students, faculty, and staff, but we don't always know which people will observe which holidays. Since I need to plan course activities in advance, I need to know in advance, if you need to miss a class or have a deadline adjusted in order to observe a holiday. Please notify me by e-mail at least 14 days in advance of any religious holiday that will affect your ability to participate in this course.