This repository contains a collection of neural network and deep learning projects built using Python and TensorFlow.
The scripts demonstrate how neural networks can be trained and applied to different machine learning tasks such as image classification and pattern recognition. These projects explore different neural network architectures and techniques including dropout regularization and training models on real datasets.
The goal of this repository is to practice deep learning concepts and understand how neural networks work using Python and TensorFlow.
- Python
- TensorFlow / Keras
- NumPy
- Matplotlib
File: neural_network.py
This project demonstrates the basic structure of a neural network.
Topics demonstrated:
- neural network architecture
- model training
- prediction and evaluation
File: neural_network_tensorflow.py
This project builds a neural network using TensorFlow and demonstrates how models can be trained using deep learning frameworks.
Features include:
- building neural networks using TensorFlow
- training and evaluating models
File: neural_network_tensorflow_2d_images.py
This script trains a neural network on two-dimensional image data and demonstrates how neural networks can classify images.
File: neural_network_tensorflow_1d_with_dropout.py
This project demonstrates the use of dropout layers in neural networks to reduce overfitting and improve model generalization.
File: neural_network_tensorflow_cifar10_2d.py
This project trains a neural network to classify images from the CIFAR-10 dataset.
The dataset contains images from categories such as:
- airplane
- automobile
- bird
- cat
- dog
The model learns to classify images into their correct categories.
File: neural_network_tensorflow_digits_mnist_and_...
This script trains a neural network to recognize handwritten digits using the MNIST dataset.
This is a classic machine learning task used to demonstrate image recognition.
File: neural_network_tensorflow_fashion_mnist_2d.py
This project trains a neural network to classify clothing images from the Fashion-MNIST dataset.
Example categories include:
- shirts
- shoes
- bags
- trousers
Install the required libraries:
pip install tensorflow
pip install numpy
pip install matplotlib
Run any script:
python filename.py
Example:
python neural_network_tensorflow_fashion_mnist_2d.py
This repository was created to practice deep learning and neural network techniques using Python.
The projects demonstrate how neural networks can be used for:
- image classification
- pattern recognition
- training deep learning models
- evaluating model performance
Sean Michaeli