Classification of Social Media Content in Algerian Dialect Using NLP and Machine Learning
Challenge Background
Social media platforms offer invaluable sources to collect real-world text content to build NLP Solutions which have become easier to build with the advances of language models. However, in countries where local dialects are commonly utilized on social media, NLP engineers encounter numerous obstacles engineers when it comes to develop language-based solutions. In such cases, customized models that handle these dialects are needed
Project Timeline
Planning and preparation
Data collection
- Data collection
- Annotation/ Building the dataset
- Annotation/ Building the dataset
- Explore NLP State of Art with Algerian dialect
- Annotation/ Building the dataset
- Explore NLP State of Art with Algerian dialect
- Building Classifiers using different techniques
- Building Classifiers using different techniques
- Evaluate and compare the performances of the different models
Model Deployment
Project Wrap up (project report and final presentation)
What you'll learn
NLP, state of art of text classification of algerian dialect, practical experience on machine and deep learning
First Omdena Local Chapter Project?
Beginner-friendly, but also welcomes experts
Education-focused
Duration: 4 to 8 weeks
Open-source
Your Benefits
Address a significant real-world problem with your skills
Build your project portfolio
Access paid projects (as an Omdena Top Talent)
Get hired at top organizations
Requirements
Good English
Suitable for AI/ Data Science beginners but also more senior collaborators
Learning mindset
Application Form
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