ziishanahmad,github

ai-chatbot-model

A simple chatbot built using TensorFlow and NLTK that can understand and respond to user queries in a conversational manner. The model uses an LSTM architecture and is trained on a dataset of conversational exchanges.

ai-detect-closed-eyes-while-driving

A deep learning project to detect closed eyes while driving using a Convolutional Neural Network (CNN).

ai-image-generator

The AI Image Generator is a Python Script that uses a pre-trained Stable Diffusion model to generate images from text prompts. This project leverages the power of the Stable Diffusion model to create high-quality images based on descriptive text inputs.

ai-llava-fine-tuned-with-scrapped-images.

This AI model scrapes images and alt tags from a website to create a dataset and fine-tunes a LLaVA VisionEncoderDecoderModel for image captioning. It leverages Hugging Face's transformers library to generate descriptive captions, demonstrating the integration of web scraping and advanced AI for practical applications.

ai-object-identifying-model

This repository contains code for building and training a Convolutional Neural Network (CNN) to classify images from the CIFAR-10 dataset. The project includes scripts for training the model, evaluating its performance, and testing it with custom images.

ai-palm-reading-model

An AI based palm reading model to read hands.

ai-web-image-scraper-trainer-model

An AI model to scrape image data and their alt parameters from a domain then train the model on that information and that predict the label of the image

diabetes-risk-prediction

A machine learning model to predict diabetes risk based on patient health data.

facial-emotion-recognition-model

A machine learning model to recognize emotions from facial expressions using image data.

handwritten-digit-recognition

A machine learning model to recognize handwritten digits using the MNIST dataset.

house-price-prediction

A machine learning model to predict house prices using the Boston Housing dataset.

human-activity-recognition

This repository contains a Long Short-Term Memory (LSTM) model for recognizing human activities using smartphone sensor data. The model is trained to classify activities into one of six categories: Walking, Walking Upstairs, Walking Downstairs, Sitting, Standing, and Laying.