Deep Learning for Mechanical Engineering

Homework 07

Due Monday, 11/06/2021, 4:00 PM

Prof. Seungchul Lee
http://iailab.kaist.ac.kr/
Industrial AI Lab at KAIST

• For your handwritten solutions, please scan or take a picture of them. Alternatively, you can write them in markdown if you prefer.

• Only .ipynb files will be graded for your code.

  • Ensure that your NAME and student ID are included in your .ipynb files. ex) IljeokKim_20202467_HW07.ipynb

• Compress all the files into a single .zip file.

  • In the .zip file's name, include your NAME and student ID. ex) DogyeomPark_20202467_HW07.zip
  • Submit this .zip file on KLMS

• Do not submit a printed version of your code, as it will not be graded.

Problem 1: Load the dataset

We will create a convolutional neural network to classify images of berries, birds, dogs, and flowers. To get started, we need to download the dataset. This dataset will be utilized for both Problem 2 and Problem 3.

• TL_CAM_train_image.npy
• TL_CAM_train_label.npy
• TL_CAM_test_image.npy
• TL_CAM_test_label.npy

(1) Load the provided dataset.

import cv2
import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf

from google.colab import drive
drive.mount('/content/drive')

Mounted at /content/drive

## your code here
#

train_image =
train_label =
test_image =
test_label =

(2) Visualize ten randomly selected images from the training dataset.

## your code here
#