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Back to week 3 page: Link
Average: 14.94
Two-thirds of the average: 9.96
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100
2, 2, 1, 0, 0, 0, 0, 1, 1, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
If your post satisfies the requirements (1), (2), (3), one of the course staff will "like" your post and you will receive 0.5 points for the post.
The past exams can be found on pages X1, X2, X3, X4, X5,
If your post satsifies the requirements (1), (2), you will receive 0.5 points for the post.
Images from Korean TV Series "Start Up" (2020) via Netflix.
Back to week 3 page: Link
# Q2 Quiz Instruction
📗 The quizzes must be completed during the lectures. No Canvas submissions are required. The grades will be updated by the end of the week on Canvas. Alternative ways to get the points are listed below in the D2 sections.
📗 Please submit a regrade request if (i) you missed a few questions because you are late or have to leave during the lecture; (ii) you selected obviously incorrect answers by mistake (one or two of these shouldn't affect your grade): Link
| Answer | Points | Out of |
| Correct | 1 | Number of Questions |
| Plausible but Incorrect | 1 | - |
| Obviously Incorrect | 0 | - |
# Game Results
📗 Round 2 of two thirds of the average game (everyone selects a number between 0 and 100 and tries to be close to two-thirds of the average of all numbers).
Average: 14.94
Two-thirds of the average: 9.96
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100
2, 2, 1, 0, 0, 0, 0, 1, 1, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
# D2 Sharing Solutions on Piazza
📗 Use the sign-up sheet: Google Sheet. You can sign up and post anonymously (anonymous Piazza posts are not anonymous to instructors).
| Requirement | M Questions | Past Exam Questions |
| List of Questions | M3Q1-10 | None |
| Due Date | June 6 | July 4 |
| Name of Post | M?Q? | X?Q? |
| Piazza Tag | m3 or d2 | m3 or d2 |
| Type of Post | public Piazza note | same |
| Include | (1) Screenshot of the question | same |
| - | (2) Detailed step-by-step solution | same |
| - | (3) Brief explanation of each step | same |
If your post satisfies the requirements (1), (2), (3), one of the course staff will "like" your post and you will receive 0.5 points for the post.
The past exams can be found on pages X1, X2, X3, X4, X5,
# D2 Discussion Topic
📗 Please create a follow-up discussion post on the Piazza (it is okay to post anonymously). No Canvas submissions are required. The grades will be updated at the end of the week on Canvas.
| Requirement | Discussion | - |
| Topic | see below | - |
| Due Date | June 6 | - |
| Type of Post | Piazza follow-up | - |
| Include | (1) Image or screenshot | - |
| - | (2) Brief discussion or explanation | (one or two sentences) |
If your post satsifies the requirements (1), (2), you will receive 0.5 points for the post.
📗 Go to the MobileNet demo: Link (TensorFlow.js) or Link (Pytorch). Find two images of the same object (or two similar objects), one of which is classified correctly and the other is classified incorrectly. Share the screenshots of the images and the labels on Piazza, and briefly discuss why you think the image may be classified incorrectly.
📗 The images can be photos you take, pictures you draw, or images you find on the Internet, you should explain in the post where you got the images from.
📗 In order for an image to be classified correctly, the object in the image must come from one of the ImageNet classes: Link.
📗 Other references in case you would like to include MobileNet in your applications: Keras: Link, TensorFlow.js: Link.
Images from Korean TV Series "Start Up" (2020) via Netflix.
Last Updated: November 18, 2024 at 11:43 PM