This repository contains a collection of machine learning projects and experiments developed using machine learning techniques. All the code and notebooks were created using Google Colab, a cloud-based Jupyter notebook environment.
Description: The Animals Project is a machine learning model developed using TensorFlow. Its main objective is to recognize and classify different types of animals. The model is trained on a dataset containing various animal images and utilizes deep learning techniques to accurately identify the animals present in new images.
Description: Project focuses on developing an advanced system capable of distinguishing between AI-generated and human-written text. This project aims to create a model that can accurately identify text origin. By leveraging cutting-edge machine learning and natural language processing techniques, this system will analyze textual features, patterns, and nuances that differentiate AI-created content from that written by humans. The outcome is expected to be highly beneficial for content verification, enhancing the integrity of digital information across various platforms.
Notebook 1: Helper Functions Notebook
Description: The Helper Functions Notebook is a collection of reusable functions that can be used in various machine learning projects and notebooks. These functions are designed to assist with common tasks such as data preprocessing, feature engineering, model evaluation, and visualization. By using the functions provided in this notebook, developers can save time and effort when working on new projects, as they can easily incorporate these helper functions into their code.
Notebook 2: Animals Notebook
Description: The Animals Notebook is a Jupyter notebook developed in Google Colab. It provides a detailed analysis and implementation of the Animals Project. The notebook includes step-by-step explanations of the model's architecture, data preprocessing techniques, model training, and evaluation. Additionally, it may contain visualizations of the model's performance and examples of animal recognition.
Notebook 3: AI / Human Detection
Description: The AI / Human Detection Notebook is a Jupyter notebook developed in Google Colab. It provides a detailed analysis and implementation of the AI / Human detection Project. The notebook includes step-by-step explanations of the model's architecture, data preprocessing techniques, model training, and evaluation. Additionally, it may contain visualizations of the model's performance and examples of animal recognition.
Clone this repository:
git clone `https://github.com/traiz-dev/machine-learning.git`
Or open the project or notebook of interest in Google Colab.