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MortadhaMannai/README.md

I'm MANAI Mohamed Mortadha 👋🏽

AI Engineer |AI Expert |XAI Engineer @Netflix |XAI Researcher @Saint Mary's university |AI Consultant @Tegus and @wivenn|Professional Technical Reviewer @Packt |2024 AI Apprentice @Google |International AI Speaker (Linkedin Top Voice * 2 )

Driven by an unwavering fascination for the transformative potential of Explainable AI (XAI), I'm captivated by the challenge of bridging the gap between complex algorithms and human understanding. My work focuses on developing interpretable models that illuminate the "why" behind AI decisions, fostering trust and transparency in automated systems. Recognized for my ability to collaborate across diverse teams and my keen attention to detail, I am committed to pushing the boundaries of XAI in an environment that nurtures both professional growth and meaningful human-AI interactions.

image

About me



Connect with me:

mannai mortadha mortadha mannai mortadha_mannai mannaimortadha898

Languages and Tools:

c cplusplus csharp django docker gcp git linux matlab mongodb mysql opencv pandas python pytorch scikit_learn seaborn tensorflow unity

MortadhaMannai

MortadhaMannai


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MortadhaMannai


🐍 A Snake Eating my Contributions Graph

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  1. Fake-news-detection-with-LSTMs-and-BERT Fake-news-detection-with-LSTMs-and-BERT Public

    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 bee…

    Jupyter Notebook 5

  2. Graph-Convolution-over-Pruned-Dependency-Trees-for-Relation-Extraction Graph-Convolution-over-Pruned-Dependency-Trees-for-Relation-Extraction Public

    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 accu…

    Python 5

  3. Natural-Language-Processing-Analyzing-GitHub-Pull-Requests Natural-Language-Processing-Analyzing-GitHub-Pull-Requests Public

    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

    Jupyter Notebook 4

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

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

    Python 3

  5. VOCAL-TRACK-EXTRACTION-USING-NEURAL-NETWORKS VOCAL-TRACK-EXTRACTION-USING-NEURAL-NETWORKS Public

    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.

    Jupyter Notebook 3

  6. BERT-Neural-Language-Interface-Explainability-Explorer BERT-Neural-Language-Interface-Explainability-Explorer Public

    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 Languag…

    Jupyter Notebook 4