MortadhaMannai

A-SHIP-OR-AN-ICEBERG-CAN-YOU-DECIDE-FROM-SPACE-

The remote sensing systems used to detect icebergs are housed on satellites over 600 kilometers above the Earth. The Sentinel-1 satellite constellation is used to monitor Land and Ocean. Orbiting 14 times a day, the satellite captures images of the Earth's surface at a given location, at a given instant in time. The C-Band radar operates at a frequency that "sees" through darkness, rain, cloud and even fog. Since it emits it's own energy source it can capture images day or night. Satellite radar works in much the same way as blips on a ship or aircraft radar. It bounces a signal off an object and records the echo, then that data is translated into an image. An object will appear as a bright spot because it reflects more radar energy than its surroundings, but strong echoes can come from anything solid - land, islands, sea ice, as well as icebergs and ships. The energy reflected back to the radar is referred to as backscatter. Here we see challenging objects to classify. We have given you the answer, but can you automate the answer to the question .... Is it a Ship or is it an Iceberg?

BERT-Neural-Language-Interface-Explainability-Explorer

Welcome to the Neural Language Interface (NLI) Explain project! This repository is dedicated to exploring and explaining the decision-making process of BERT models in the context of Natural Language Inference (NLI) tasks. We employ Feature Interaction methods to shed light on why BERT makes specific predictions in NLI.

Comparative-Analysis-of-Equity-Crowdfunding-Expenditure-Across-OECD-Nations-Python-and-R-Approach

This project aims to perform a comprehensive analysis of the differences in money spent on "Equity Crowdfunding" projects across OECD countries.

Disaster-Risk-Monitoring-Using-Satellite-Imagery-and-Nvidia-Libraries

Learn how to build and deploy a deep learning model to automate the detection of flood events using satellite imagery. This workflow can be applied to lower the cost, improve the efficiency, and significantly enhance the effectiveness of various natural disaster management use cases.

EvolveGCN-Evolving-Graph-Convolutional-Networks-for-Dynamic-Graphs-

This repository contains the code for EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs, published in AAAI 2020.

Fake-news-detection-with-LSTMs-and-BERT

well Social media has affected society during the last decade by providing free milieus for everyone to share their thoughts, ideas, and also news. As a negative effect, these environments have been used for propagation of low-quality, content-bare, and even outright “Fake” news. Spreading of Fake news has extreme effects on people’s minds and societies, such as decreasing one’s trust to all sources of news, making readers defensive against most news channels,The Fight Against Fake News with Deep Learning Fake news detection with LSTMs and BERT etc. This is why recently the detection of Fake news has become one of the top trends in the field of research. Referring to one of the latest works on this area, detecting Fake news in social media has exclusive features which cannot be found in traditional methods and approaches for reality detection so this work represent

Graph-Convolution-over-Pruned-Dependency-Trees-for-Relation-Extraction

Graph Convolution over Pruned Dependency Trees for Relation Extraction" is a sophisticated approach that leverages graph convolutional networks (GCNs) on pruned dependency trees to enhance the accuracy of relation extraction tasks

Housing-Prices-prediction

it's my personal work for Week 1Assignment Housing Prices: ( from coursera course :Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning)..In this exercise Itry to build a neural network that predicts the price of a house according to a simple formula. Imagine that house pricing is as easy as: A house has a base cost of 50k, and every additional bedroom adds a cost of 50k. This will make a 1 bedroom house cost 100k, a 2 bedroom house cost 150k etc. I create a neural network that learns this relationship so that it would predict a 7 bedroom house as costing close to 400k etc. Hint: my network might work better if i scale the house price down. i don't have to give the answer 400...it might be better that i created something that predicts the number 4, and then the answer is in the 'hundreds of thousands' etc.

Natural-Language-Processing-Analyzing-GitHub-Pull-Requests

This project covers the concepts of : Topic Modelling using LDA Clustering through tf-idf and BoW Dimension reduction through t-SNE and truncated SVD Classification and Regression algorithms

VOCAL-TRACK-EXTRACTION-USING-NEURAL-NETWORKS

There are four models in this project: Deep Clustering Model, Hybrid Deep Clustering Model, U-net Model and UH-net Model. Models are trained on DSD100 dataset. The project is based on PyTorch.

MortadhaMannai/MIC-Workshop-Application-of-Generative-IA-in-the-Real-Word

Welcome to the MIC-Workshop-Application-of-Generative-IA-in-the-Real-Word repository! Here, you'll find comprehensive resources, code, and instructions for exploring and building AI applications using cutting-edge language models (LLMs).

MortadhaMannai/Google-Foobar-Challenge-Experience-2024

Hey Everyone! I wanted to share that I participated in the Google 2024 Foobar challenge and successfully completed all 4 levels! (Still 1a to go 🔥). I'll be sharing all the code snippets, notes, and challenges on my GitHub account and my LinkedIn feed soon!

MortadhaMannai/MortadhaMannai

Driven by an unwavering fascination for AI's transformative power, I'm captivated by its intricate fusion of data and algorithms.

MortadhaMannai/DynaGraphX

DYnamic Attributed Node rolEs (DYANE) is an attributed dynamic-network generative model based on temporal motifs and attributed node behavior.

MortadhaMannai/Awesome-LLM

Awesome-LLM: a curated list of Large Language Model

MortadhaMannai/deepface

A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python

MortadhaMannai/dispatch

All of the ad-hoc things you're doing to manage incidents today, done for you, and much more!

MortadhaMannai/FaceNetX-Face_Recognition_w_DeepFace-

This code provides an implementation of face recognition using the DeepFace library and OpenCV. It allows you to perform face recognition on both static images and real-time video from a webcam.

MortadhaMannai/FriendLinker-Uncovering-Indirect-Friendship-Relations-in-Ego-Networks

The FriendLinker project focuses on identifying indirect composite relations within an ego network, specifically exploring the Friend relationship to uncover connections between different egos.

MortadhaMannai/HR-Employee-Dataset-Analysis-Using-Tableau

The objective of the project is to create an engaging dashboard designed to visualize meaningful insights derived from HR data. This dashboard encompasses comprehensive employee information, including job status, performance metrics, reasons for resignation, and more.

MortadhaMannai/huggingface.js

Utilities to use the Hugging Face Hub API

MortadhaMannai/I-m-in-the-Top-3O-of-top-github-users-in-Tunisia-

Check your ranking in GitHub! Don't forget to star ⭐ this repository.

MortadhaMannai/IdentityGenderNet

Simple face gender detection for an online meeting, modified based on face-emotion

MortadhaMannai/IntelliMap-Graph-Based-Monitoring

Detecting malicious actions on a network with the use of artificial intelligence is called intelligent monitoring. To be more precise a number of standard attack techniques can be detected by collecting various information from the network.

MortadhaMannai/linkedin_orgchart_scraper

A Python automation that allows to extract company names and roles from an input compan, using Selenium and BSoup. It opens many ways to increase its functionality such as getting emails, persona urls, numbers of people in the company, doing multiple searches and so on.

MortadhaMannai/llvm-project

The LLVM Project is a collection of modular and reusable compiler and toolchain technologies. This fork is used to manage Apple’s stable releases of Clang as well as support the Swift project.

MortadhaMannai/LokoAI-Enhanced-ScikitLLM-Extension

The "LokoAI-Enhanced: ScikitLLM Extension" project aims to bolster the capabilities of LokoAI by integrating the advanced functionalities of the ScikitLLM library. This extension intends to enhance LokoAI's feature set by incorporating the specialized tools and algorithms offered by ScikitLLM.

MortadhaMannai/metacat

MortadhaMannai/metaflow-service

:rocket: Metadata tracking and UI service for Metaflow!

MortadhaMannai/ml-mobileclip

This repository contains the official implementation of the research paper, "MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training" CVPR 2024

MortadhaMannai/netflix.github.com

MortadhaMannai/nltk

NLTK Source

MortadhaMannai/open-sdg

A platform for collecting and disseminating data for the Sustainable Development Goal global indicators.

MortadhaMannai/Social-Sales-Forecast-Improving-Social-Network-ads

Prediction system to predict which user is going to buy a product displayed on a social media advertisement using random forest classification.

MortadhaMannai/structured-additive-IR

An intermediate program representation, based on MLIR and designed to express implementation decisions on a program without losing the high-level structure of the code. It encodes implementation choices as attributes added on to existing operations (hence "additive" in the name).

MortadhaMannai/super-gradients-fork

Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.

MortadhaMannai/transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

MortadhaMannai/unstructured

Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.

MortadhaMannai/XAI_GridSearch_CatsVSDogs_EffNetV2

A project focusing on binary classification using Explainable Artificial Intelligence (XAI) methods, specifically SHAP (SHapley Additive exPlanations), and Grid Search for hyperparameter tuning. The project utilizes EfficientNetV2-B0 architecture on the Cat VS Dog dataset.

MortadhaMannai/XPyChatGPT-API-Rebuilding

This repository contains code for building a terminal-based chatbot using OpenAI's recently released ChatGPT API (https://openai.com/blog/introducing-chatgpt-and-whisper-apis). The code is written in Python and uses the OpenAI Python library