This post offers a foundational template for implementing a neural network for multi-class classification tasks using TensorFlow and PyTorch, specifically tailored for tabular data. It serves as a ready-to-use boilerplate code to quickly initiate such projects, saving time by eliminating the need to search through past work or generate new code from ChatGPT.
First, the data…
from ucimlrepo import fetch_ucirepoiris = fetch_ucirepo(id=53)
X = iris.data.features
y = iris.data.targets
print(X)
"""
sepal length sepal width petal length petal width
0 5.1 3.5 1.4 0.2
1 4.9 3.0 1.4 0.2
2 4.7 3.2 1.3 0.2
3 4.6 3.1 1.5 0.2
4 5.0 3.6 1.4 0.2
.. ... ... ... ...
145 6.7 3.0 5.2 2.3
146 6.3 2.5 5.0 1.9
147 6.5 3.0 5.2 2.0
148 6.2 3.4 5.4 2.3
149 5.9 3.0 5.1 1.8
[150 rows x 4 columns]
"""
print(y)
"""
class
0…
Be the first to comment