SarahBenabdallah

SarahBenabdallah's Stars

• Fatma-Chaouech/PokeMLOps

  An all-in-one MLOps solution for managing and deploying your ML models with ease. Streamline your workflow, automate training and deployment pipelines, monitor model performance, and collaborate seamlessly with your team.

  Language:Python161

• csdemeras/FSMap

  Dataset corresponding to paper "Single Fusion Image from Collections of Fruit Views for Defect Detection and Classification"

  21

• khanhnamle1994/cracking-the-data-science-interview

  A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep

  Language:Jupyter Notebook3.6k1k

• youssefHosni/Data-Science-Interview-Preperation-Resources

  Resoruce to help you to prepare for your comming data science interviews

  953205

• INSATunisia/TP-BigData

  Language:JavaScript1015

• spmallick/learnopencv

  Learn OpenCV : C++ and Python Examples

  Language:Jupyter Notebook21k11.6k

• balajisrinivas/Gender-Detection

  Gender Detection using Python Keras and OpenCV on live camera

  Language:Python4673

• sherlockchou86/face_properties_based_vggface

  Age, gender and race estimation based on VGGFace using Tensorflow 2.0

  Language:Python155

• lavsolanki/Age-Gender-estimation

  Age estimation is the determination of a person’s age based on biometric features. Although age estimation can be accomplished using different biometric traits, our work is focused on facial age estimation that relies on biometric features extracted from a person’s face. In the area of computerized analysis of facial images for recognition, ethnicity classification, gender recognition, etc. the age estimation is a barely explored part. However recently the interest in this subject has significantly increased, due to its practical applications. For example there are age limitations for driving a car, buying alcohol, cigarettes, films, video games, etc. which should be obeyed, but the human skills of age estimation are very limited. So a computer system, which supports the responsible persons, would be helpful. It is well known that the human-computer interaction varies for different age groups, thus a system which automatically adapts its interface to the age of the current user would clear this problem. Face detection: To detect whether an image represent a face i.e. the general structure of face or not. General structure include forehead, eyes, nose, lips, chin etc.

  Language:Python44

• yassineelkhadiri/Arabic-Sentiment-Analysis

  This notebook aims to explore the topic of Arabic sentiment analysis, using MultinomialNB models trained on the arabic-sentiment-twitter-corpus and evaluated on 3 other sentiment-labelled Arabic datasets (SS2030 ,100k Arabic Reviews and ArSAS.

  Language:Jupyter Notebook3

• ashishpatel26/Andrew-NG-Notes

  This is Andrew NG Coursera Handwritten Notes.

  Language:Jupyter Notebook2.5k990

• Yuleii/Yuleii.github.io

  My personal blog(always under construction).

  Language:SCSS2221

• MichaelCade/90DaysOfDevOps

  This repository started out as a learning in public project for myself and has now become a structured learning map for many in the community. We have 3 years under our belt covering all things DevOps, including Principles, Processes, Tooling and Use Cases surrounding this vast topic.

  Language:Shell26.4k6.3k

• hajali-amine/cheat-sheets

  A place for all of my cheat sheets.

  Language:JavaScript246

• Saief1999/CheatSheets

  This repository contains my personal Cheat Sheets

  Language:TypeScript191

• Elouaeramine/SNMP

  A Python Script allowing administrators to collect information about devices using Simple Network Management Protocol.

  Language:Python4

• Elouaeramine/TPJ2EE

  Language:Java2