Deep Learning Courses

A Wildfire Detection System that integrates machine learning models with satellite imagery, camera feeds, and weather data to predict and detect wildfires effectively.

This project is designed to detect image forgery using various techniques and tools. It includes a Flask web application that allows users to upload images and check their authenticity. The project utilizes the CASIA2 dataset from Kaggle.

Deep Learning Courses

This project involves an exploratory analysis of the capabilities of Convolutional Neural Networks (CNNs) for image classification, using a dataset of animal images. The goal is to understand how well CNNs can distinguish between different types of animals based on their images.

Grayscale image colorization using a U-Net CNN (with VGG-19) and perceptual loss.

Collection of free Notes,Courses,Videos,Projects,Articles and Repos Links To learn Machine learning ,Deep learning,Python,SQL,CNN,NLP,GAN,GNN,Transfomers,Flask,Django,and End to End Machine learning Projects

This is a web application built with Flask for detecting malaria in microscopic images of blood samples. It uses a deep learning model trained on TensorFlow/Keras to classify images as either infected (parasitized) or uninfected.

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

Defect detection on metal shaft surfaces using Convolutional Neural Network

Real time face-mask detection using Deep Learning and OpenCV

Repositorio de mi aplicación móvil hecha con React Native cargando un modelo entrenado con Keras.

Neural network that identifies and labels vegetables

A fall detection system using deep learning and Kalman filters to process signals from the Sysfall dataset. This project leverages advanced techniques to accurately detect falls, improving safety and response times in various environments.

This project aims to study a public dataset on pneumonia detection based on a binary classification problem. I will perform a preprocessing phase, create a deep learning model from scratch, evaluate it with a transfer learning technique and complete this study with a grad cam integration.

Constructed an advanced deep learning model utilizing TensorFlow and CNN to precisely classify bird species from audio inputs. Leveraging Librosa for audio processing, the model is trained on extensive bird sound datasets to ensure robust performance. Integrated with Hugging Face, our application facilitates seamless uploading of bird sound samples

An innovative traffic sign detection technique for precise and efficient identification

For the practical implementation of this project , i have created an app on Streamlit and uploaded on Streamlit Cloud Cloud

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

Superhero Classifier Web App using Streamlit built on a custom CNN Image classifier