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👋 Hi, it's Junior! 📊 Passionate Data Scientist, I turn data into captivating stories. 💻 Explore my projects here.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Text_Classification_with_PySpark
May 19, 2024 – May 19, 2024
Multi-class text classification using PySpark and Machine Learning in Python
View ProjectML_with_PySpark
May 17, 2024 – May 17, 2024
Explore how to do machine learning with PySpark and Python.
View ProjectDokcerize_apps_python
May 11, 2024 – May 11, 2024
Ce projet explique comment cloner un projet machine learning existant et le deployer avec Docker Desktop.
View ProjectNLP-app-using-FastAPI-and-jinja2
April 29, 2024 – May 10, 2024
This repository contains code for a sentiment analysis model that can classify texts as expressing one of five emotions: joy, anger, love, sadness, or fear.
View ProjectR-shiny
April 23, 2024 – April 28, 2024
Deploying the iris predictor web app built with R shiny
View Projectprogrammer_en_pyspark
April 13, 2024 – May 16, 2024
Manipulation et analyse de gros volumes de données( 8 millions d'observations)
View Projectdev_app
November 26, 2023 – May 11, 2024
Ce projet a été développé pour prédire le salaire annuel des développeurs informatiques dans différents pays, en se basant sur leur profil professionnel.
View Projectrecommender_system
November 24, 2023 – May 10, 2024
Ce projet est une application de système de recommandation utilisant la similarité cosinus pour recommander des éléments similaires à partir d'une base de données Kaggle.
View Projectapp_credit
November 22, 2023 – April 28, 2024
Ce projet de data science vise à développer un modèle de prédiction pour évaluer l'admissibilité des demandeurs de prêt immobilier.
View ProjectSentiSCAN
November 6, 2023 – November 6, 2023
Création d'une API Web via FastAPI qui effectue une analyse de sentiments sur les commentaires YouTube en utilisant un modèle de machine learning.
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and demonstrate a strong interest in data science and machine learning. However, the lack of team-based projects or professional experience makes it difficult to fully assess cultural fit. The projects show initiative and a drive to learn new technologies relevant to the target role. The diversity of projects (NLP, recommendation systems, predictive modeling) suggests a broad interest within the data science domain.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate an ability to work on self-directed projects, but collaboration, stress handling, and work attitude cannot be evaluated without psychometric test results or interview data.