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Muhammad Fathi's Projects

arabic-stop-words icon arabic-stop-words

Largest list of Arabic stop words on Github. أكبر قائمة لمستبعدات الفهرسة العربية على جيت هاب

computer-science icon computer-science

:mortar_board: Path to a free self-taught education in Computer Science!

face_recognition icon face_recognition

The world's simplest facial recognition api for Python and the command line

fairseq icon fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

hackerrank icon hackerrank

HackerRank solutions on data structures and algorithms to practice for coding interview questions.

lans.py icon lans.py

Inject code, jam wifi, and spy on wifi users

lectures-labs icon lectures-labs

Slides and Jupyter notebooks for the Deep Learning lectures at M2 Data Science Université Paris Saclay

localstack icon localstack

💻 A fully functional local AWS cloud stack. Develop and test your cloud & Serverless apps offline!

nlp-progress icon nlp-progress

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

scrapy icon scrapy

Scrapy, a fast high-level web crawling & scraping framework for Python.

study-of-detection-brain-tumor-with-machine-learning icon study-of-detection-brain-tumor-with-machine-learning

Tumor is an uncontrolled growth of tissues in any part of the body. Tumors are of different types and hence they have different treatments. Detection of tumor in the earlier stages makes the treatment possible. Here we review different segmentation methods associated with feature extraction from Magnetic Resonance Imaging (MRI) of brain. We also discuss different machine learning and classification algorithms that use to classify normal and cancerous tissues. Finally, we propose an automatic tumor detection system

tensorflow icon tensorflow

Computation using data flow graphs for scalable machine learning

viberr icon viberr

Viberr is an application that let's you upload, store, and play all of your music from the cloud.

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