mhabibi's repositories
LIME-for-Time-Series
LIME for TimeSeries enhances AI transparency by providing LIME-based interpretability tools for time series models. It offers insights into model predictions, fostering trust and understanding in complex AI systems.
CNN-Predictor-for-Malaria_Cells-LIME-CAM
Enhanced CNN model for malaria cell classification, featuring Class Activation Mapping (CAM) as a non-agnstic technique for anomaly localization and LIME (Local Interpretable-agnostic Explanation) for interpretability, ensuring high accuracy and transparent AI diagnostics.
DeepLearning-VAE
Exploring the depths of generative learning with a $\beta$-Variational Autoencoder ($\beta$-VAE) applied to the MNIST dataset for robust digit reconstruction and latent space analysis.
Neural-Compression-with-Autoencoders
Exploring advanced autoencoder architectures for efficient data compression on EMNIST dataset, focusing on high-fidelity image reconstruction with minimal information loss. This project tests various encoder-decoder configurations to optimize performance metrics like MSE, SSIM, and PSNR, aiming to achieve near-lossless data compression.
Automated-Cell-Semantic-Segmentation-with-UNet
A machine learning solution for automating nucleus detection in biomedical images, leveraging the U-Net architecture to accelerate medical research and disease treatment discovery.
Capstone-Project-IBM
A data-driven project to predict the success of Falcon 9 rocket landings, crucial for cost analysis and competitive strategy in the space industry. Involves data manipulation in Pandas, JSON data processing, and insightful analysis using Python.
DeepLearning
Python code accompanying the course "A deep understanding of deep learning (with Python intro)"
fastapi-questionnaire-api
A FastAPI application to manage and retrieve questionnaire data
gpu-python-tutorial
GPU Development in Python 101 tutorial
InvertedPendulumSDS-Ben
Projektausarbeitung zum Wahlmodul - Sondergebiete der Simulation - WS21/22
machine-learning-for-physicists
Code for "Machine Learning for Physicists 2020" lecture series
Variational_AutoEncoders
Various VAEs
ML_Turb_CR_DeepLearning
PyTorch CNNs and U-nets trained on astrophysical turbulence simulations
MLAlgorithms_check
Minimal and clean examples of machine learning algorithms implementations
movie-recommendation-systems
A comprehensive collection of movie recommendation systems, implementing collaborative filtering, content-based filtering, weighted average, and more.
pbdl-book-PINN
Welcome to the Physics-based Deep Learning Book (v0.2)
PlasmaPy
An open source Python package for plasma research and education
postpic-epoch
The open-source particle-in-cell post-processor.
pyppt
Python interface for adding figures to Microsoft PowerPoint presentations on-the-fly.
TelescopeML-forked
Deep Convolutional Neural Networks and Machine Learning Models for Analyzing Stellar and Exoplanetary Telescope Spectra