Sea Animals Classification using Deep Convolutional
Neural Networks and Transfer Learning
Thanks for visiting my notebook
🔬Overview
Most life forms evolved initially in marine habitats. By volume, oceans provide
about 90% of the living space on the planet. The earliest vertebrates
appeared in the form of fish, which live exclusively in water. Some of these
evolved into amphibians, which spend portions of their lives in water and
portions on land. One group of amphibians evolved into reptiles and
mammals and a few subsets of each returned to the ocean as sea snakes, sea
turtles, seals, manatees, and whales. Plant forms such as kelp and other
algae grow in the water and are the basis for some underwater ecosystems.
Plankton forms the general foundation of the ocean animal chain, particularly
phytoplankton which are key primary producers.Source
❗Author's Note:
Make sure to run the cells from top to bottom with a GPU accelerator. There
are some linux commands present in some cells so this is important to take
into account. Also, any suggestions, comments and recommendations to
improve the notebook will be highly appreciated. Cheers!
🏗�Import Necessary Libraries
In [1]:
# Import Data Science Libraries
import numpy as np
import pandas as pd
import tensorflow as tf
from sklearn.model_selection import train_test_split
