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Image Classification of 250 Bird Species dataset

In this project, I trained a ResNet-n (n=9) neural networks architecture with a different layers to classify a diverse set of 250 Bird Species from the Kaggle dataset. In this project, I used the 250 Birds Species Dataset, which consists of 250 bird species. 35215 training images, 1250 test images(5 X 250 species) and 1250 validation images(5 X 250 species). All images are 224 X 224 X 3 color images in jpg format. Also includes a “consolidated” image set that combines the training, test and validation images into a single data set.

Let's start by installing jovian library for link my notebook with my profile.

# Jovian Commit Essentials
# Please retain and execute this cell without modifying the contents for `jovian.commit` to work
!pip install jovian --upgrade -q
import jovian
# jovian.utils.colab.set_colab_file_id('1lgTTsO6CuYS49m24tKeRN6uSpkipyE3Q')

Mounting the google drive