This repository contains code and resources related to Convolutional Neural Networks (CNN) using TensorFlow.
★ A Convolutional Neural Network is a specialized type of neural network designed for processing structured grid data, such as images. It uses convolutional layers to automatically and adaptively learn spatial hierarchies of features, allowing it to efficiently learn patterns.
★ TensorFlow is an open-source machine learning framework developed by the Google Brain team. It provides a comprehensive set of tools for building and deploying machine learning models, making it a popular choice for implementing CNNs.
★ Neural Networks, the foundation of deep learning, are computational models inspired by the human brain's neural structure. They consist of interconnected nodes (neurons) organized in layers, each layer contributing to the extraction of features and learning patterns from the input data.
This project serves as a practical exploration of Convolutional Neural Networks and TensorFlow. The code and resources here are a result of my learning journey, and I am thrilled to be part of the continuous adventure of mastering TensorFlow and neural networks.
Feel free to explore the code, experiment, and learn along with me!