Welcome to the Machine-Learning repository! This project leverages transfer learning using the MobileNetV2 model to classify images from a publicly available dataset. The objective is to fine-tune a pre-trained model to achieve accuracy 0.8 on our specific dataset.
The project utilizes the following technologies:
- Python: The main programming language used for implementing the machine learning models.
- Jupyter Notebook: For creating and sharing documents that contain live code, equations, visualizations, and narrative text.
- TensorFlow & Keras: For building and training the machine learning models.
- Pandas: For data manipulation and analysis.
- NumPy: For numerical computing.
- Matplotlib & Seaborn: For data visualization.
The dataset used in this project is obtained from Kaggle. It contains various features and target variables that will be used for training and testing the machine learning models. Dataset Source: Kaggle - Capstone Dataset
Project Link: https://github.com/RasaGram/Android-Development