Pinned Repositories
100-Days-Of-ML-Code
100 Days of ML Coding
AI-Basketball-Shot-Detection-Tracker
Machine learning and computer vision to detect and analyze basketball shots in real-time (2023)
AI-Vengers
ailab
Experience, Learn and Code the latest breakthrough innovations with Microsoft AI
alphafold
Open source code for AlphaFold.
ambianic-edge
Core runtime engine for the Ambianic Box IoT/Edge device. Privacy preserving incident monitoring via camera and other sensors. Detect people, falls, objects, anomalies.
amodem
Audio MODEM Communication Library in Python
applied-ml
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
avatarify
Avatars for Zoom, Skype and other video-conferencing apps.
awesome-self-supervised-learning
A curated list of awesome self-supervised methods
RamiHadji's Repositories
RamiHadji/Coursera-Google-Cloud-Platform-Fundamentals-Core-Infrastructure
About this Course This course introduces you to important concepts and terminology for working with Google Cloud Platform (GCP). You learn about, and compare, many of the computing and storage services available in Google Cloud Platform, including Google App Engine, Google Compute Engine, Google Kubernetes Engine, Google Cloud Storage, Google Cloud SQL, and BigQuery. You learn about important resource and policy management tools, such as the Google Cloud Resource Manager hierarchy and Google Cloud Identity and Access Management. Hands-on labs give you foundational skills for working with GCP.
RamiHadji/Covid19LiveTrackerApp
This covi19 (CORONA) Live Tracker and Awareness App
RamiHadji/Deep-Android-Malware-Detection
Code for Deep Android Malware Detection paper
RamiHadji/did.ai
Decentralized Identity & Artificial Intelligence
RamiHadji/MachineVideoEditor
This repository does not contain code, its purpose it for issue tracking and wiki
RamiHadji/Malware-Detection-using-Deep-Learning
RamiHadji/Malware-Detection-using-Deep-Learning-1
Firstly, we generate images from benign and malware executable files. Secondly, by using deep learning, we train a model to detect malware files. Then, by the trained model, we try to classify a file as malware or not. By using malware images and deep learning, we can detect malware fast since we do not need any static analysis or dynamic analysis.
RamiHadji/Malware_Detection_Using_Deep_Learning
An approach to detect Malware Files using Deep Learning
RamiHadji/pentest
RamiHadji/PynAuth
RamiHadji/SkCodecFuzzer
Fuzzing harness for testing proprietary image codecs supported by Skia on Android
RamiHadji/submit50-cs50-problems-2020-x-cash
RamiHadji/tweets_analyzer
Tweets metadata scraper & activity analyzer
RamiHadji/Unified-Threat-Management
This is a scalable way of protecting remote/branches with top notch security solution
RamiHadji/web_cv
سيرة ذاتية 👨⚖️👩✈️👨🚒🕵️♀️👮👨🏫👨🚀👨🎨👩🏭 احترافية ويب HTML5, CSS3 بتصميم مرن Respnsive Design مناسبة لجميع أحجام الشاشات 💻📱