Randa LAKAB

Data Scientist

https://talent.gravityer.com/randa-lakab

Data Science Student | UI/UX Designer & Front-end Dev | Passionate about AI & Human-Centred Design | Lifelong learner

Algeria

Key Strengths

Demonstrated proficiency in Python for machine learning and data analysis tasks.
Experience with various machine learning models including ANN, CNN, and Linear Regression.
Practical application of ML in projects like crop recommendation and plant disease detection.
Familiarity with Flask for building web applications integrating ML models.
Exposure to R for data analysis and visualization.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are primarily personal and demonstrate a strong interest in machine learning and data science. The diversity of projects (medical data, image classification, crop recommendation, web apps) indicates a broad curiosity and willingness to explore different applications of data science. However, the lack of team-based projects or professional experience makes it difficult to fully assess cultural fit in a collaborative work environment.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insights into logical reasoning, work attitude, stress handling, or team collaboration.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

McCulloch-Pitts-Neuron-and-Logic-Gates

April 2, 2026 – Present

McCulloch-Pitts-Neuron-and-Logic-Gates — Dev.to repository

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Fashion_mnist_ann

April 1, 2026 – Present

This project uses a simple Artificial Neural Network (ANN) to classify clothing images from the Fashion MNIST dataset.

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Plant-disease-detection

March 29, 2026 – Present

Plant Leaf Disease Detection using CNN, TensorFlow/Keras and Flask.

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MNIST-ANN

March 24, 2026 – Present

MNIST-ANN — Dev.to repository

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Multiple-Linear-Regression

March 23, 2026 – Present

Multiple-Linear-Regression — Dev.to repository

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Crop-recommendation

March 17, 2026 – Present

ML web app that recommends the optimal crop based on soil & climate data . Flask REST API + scikit-learn (98.86% accuracy) · 22 crops · 6 models compared

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User-manager-bootstrap

March 6, 2026 – Present

This project demonstrates how to combine Flask with Bootstrap to create a functional and visually appealing CRUD application.

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Cloud-microproject

February 22, 2026 – Present

Cloud-microproject — Dev.to repository

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AFC-Algorithm

February 14, 2026 – Present

AFC-Algorithm — Dev.to repository

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Anemia-Analysis

July 29, 2025 – October 3, 2025

Medical blood data analysis using R and ggplot2

View Project

Key Strengths

Demonstrated proficiency in Python for machine learning and data analysis tasks.
Experience with various machine learning models including ANN, CNN, and Linear Regression.
Practical application of ML in projects like crop recommendation and plant disease detection.
Familiarity with Flask for building web applications integrating ML models.
Exposure to R for data analysis and visualization.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insights into logical reasoning, work attitude, stress handling, or team collaboration.

Randa LAKAB

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit