Final Course Project, Crawler + ANN

Natural Language Processing project exploring the classification problem of 'triggering' content on social media.

"Developing a deep learning model for fashion classification, distinguishing clothing items with high accuracy, leveraging convolutional neural networks for image recognition and feature extraction."

👨🏻‍💻 I'm excited to share my journey as an AI ML trainee at Metafiser. This opportunity allowed me to dive deep into the world of Artificial Intelligence, gaining hands-on experience with various innovative projects and datasets. In this repository, you will find all my projects and training files documenting this exciting journey! 💫

Python package that provides a full range of functionality to process and analyze vibrational spectra (Raman, SERS, FTIR, etc.).

Depression Detect is a web app which enables clinicians to use sensing technologies with a focus on acoustic characteristics and facial landmarks to detect depression.

For-rest from Fires (Fire Detection Model using Deep Learning)

There are several different types of traffic signs like speed limits, no entry, traffic signals, turn left or right, children crossing, no passing of heavy vehicles, etc. Traffic signs classification is the process of identifying which class a traffic sign belongs to

This project focuses on brain tumor segmentation using MRI images, employing a deep learning approach with the U-Net architecture. The model is designed to accurately segment tumor regions from non-tumor areas in MRI scans, automating the traditionally manual and error-prone process. By leveraging the LGG MRI Segmentation Dataset from Kaggle.

A deep learning-based application for skin disease detection and classification.

hyper-sinh: An Accurate and Reliable Activation Function from Shallow to Deep Learning in TensorFlow, Keras, and PyTorch

An intuitive and user-friendly web application developed using Python to classify X-ray images and identify if they indicate the presence of pneumonia.

An End-to-End project for COVID-19 detection through X-ray image of the chest.

Detection and Classification of Eye Diseases: Diabetic Retinopathy, Cataract, and Glaucoma Using CNN

This project implements a Convolutional Neural Network (CNN) to classify handwritten digits from the MNIST dataset. The model is built using TensorFlow and Keras.

Early Detection of Diabetic Retinopathy System, an application, uses machine learning to assess diabetic retinopathy risk. Input your health data and get results within seconds: Ranging from ['Mild', 'Moderate', 'Severe', 'No_DR']

Simple implementation of Variational Autoencoder on MNIST with keras number Dataset

To develop an application which could be used by especially abled person to be able to convey their hand sign or gesture language into speech and aid an ordinary person to translate speech to gesture or hand sign language in order to make the communication more fluent

It can recognize all living beings, from humans to animals. Except ur ex, i'm still working on that algorithm.