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.
Compress all the files into a single .zip file.
Do not submit a printed version of your code, as it will not be graded.
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.
(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')
## your code here
#
train_image =
train_label =
test_image =
test_label =
(2) Visualize ten randomly selected images from the training dataset.
## your code here
#