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Hi there πŸ‘‹, I'm Youssef Mouraffa

Data Scientist | Deep Learning | Computer Vision | NLP Enthusiast πŸš€

Passionate about leveraging data to derive meaningful insights.

πŸ“ Currently in Kiel, Germany πŸ‡©πŸ‡ͺ

Contact Information πŸ“¬

GitHubΒ  EmailΒ  Digital ResumeΒ  LinkedIn

About Me 🌟

I'm a dedicated Data Scientist passionate about Deep Learning, Computer Vision, and Natural Language Processing (NLP). I thrive on extracting valuable insights from data to solve real-world problems.

Skills and Technologies πŸ› οΈ

Python TensorFlow PyTorch OpenCV NLP Data Viz YOLO scikit-learn Keras NumPy Pandas Matplotlib Seaborn Langchain

C C++ Matlab CNN RNN LLM GANs

Git Amazon Docker SQL/Mysql

Arduino Raspberry Pi Linux

Let's Connect 🀝

Looking forward to connecting with like-minded professionals and collaborating on exciting projects!

YOUSSEF MOURAFFA's Projects

cameracalibration-using-the-zhang-s-methode icon cameracalibration-using-the-zhang-s-methode

This program implements a camera calibration algorithm based on Zhang's method. It allows you to calibrate your camera, estimate its intrinsic and extrinsic parameters, and correct for lens distortion effects.

cancer_classification_svm icon cancer_classification_svm

A comprehensive Jupyter notebook project that uses Support Vector Machines (SVM) for the classification of breast tumors into malignant or benign categories. The notebook includes data exploration, visualization, model training, and evaluation, providing insights into breast cancer diagnosis using machine learning.

cifar10-image-classification-comparing-cnn-and-ann-models icon cifar10-image-classification-comparing-cnn-and-ann-models

This project demonstrates image classification using the CIFAR10 dataset in TensorFlow. It compares the performance of a simple Artificial Neural Network (ANN) and a Convolutional Neural Network (CNN) for this task. The purpose is to understand why CNNs are preferred over ANNs for image classification.

data-scientist-daily-helper-functions- icon data-scientist-daily-helper-functions-

Welcome to the Data Scientist Daily Helper Functions repository! πŸš€ This collection houses Python helper functions simplifying common tasks in data scienceβ€”image processing, natural language processing, machine learning, and general programming. Boost your productivity with this versatile toolkit.

digital-resume-with-streamlit icon digital-resume-with-streamlit

Welcome to my digital resume! I'm Youssef Mouraffa. This Streamlit-powered platform showcases my expertise in data science, machine learning, and computer vision. Dive in to explore my career journey and skill set!

face-detection-using-arduino icon face-detection-using-arduino

I'm so glad to share my first OpenCV project using Arduino, It's a simple program for detecting faces and turning on a LED. If there is a detection then the green LED is on otherwise, the yellow LED lights up

generative-adversarial-networks-gans-for-anime-image-generation icon generative-adversarial-networks-gans-for-anime-image-generation

Embark on a creative journey with AnimeGAN, a project harnessing Generative Adversarial Networks (GANs) to generate captivating anime-style images. Witness the dynamic interplay of a generator and discriminator, resulting in the creation of high-quality, indistinguishable-from-real anime art. Explore the artistry of AI in this captivating endeavor!

handwritten_digits_classifier icon handwritten_digits_classifier

A neural network-based approach for handwritten digit classification using the MNIST dataset. Explore different models, techniques, and architectures to achieve accurate digit recognition.

knn-from-scratch-iris-classifier icon knn-from-scratch-iris-classifier

This repository features a Python K-Nearest Neighbors (KNN) implementation from scratch, with an explanatory notebook. See KNN in action on the Iris dataset and explore data visually in a dedicated notebook. A hands-on guide to understanding and applying KNN!

linearregression_cpp_fromscratch icon linearregression_cpp_fromscratch

This repository contains a simple implementation of linear regression from scratch in C++ and includes Python scripts for data generation and error visualization.

perceptron-with-one-hidden-layer icon perceptron-with-one-hidden-layer

This project is an implementation of a Perceptron with one hidden layer and softmax function. The purpose of this project is to build a neural network that can classify input data into different categories

polynomial_regression_from_scratch icon polynomial_regression_from_scratch

An educational deep dive into machine learning, building a polynomial regression model from the ground up with Python. This repo offers hands-on experience with the fundamentals of regression analysis, gradient descent optimization, and data visualization.

realtime-object-detection-yolov5-and-streamlit icon realtime-object-detection-yolov5-and-streamlit

Comprehensive object detection using YOLOv5, trained from scratch. Includes data preparation, YOLOv5 training on 20 labels, and testing on images/videos. Utilizes Google Colab's V100 GPU for robust detection.

sentimental_analysis_logregclassification icon sentimental_analysis_logregclassification

An advanced, Python-based sentiment analysis tool utilizing logistic regression to accurately classify Twitter messages. This project demonstrates sophisticated NLP techniques and model optimization for real-world social media data analysis.

skimlit-nlp-model-for-sentence-classification-in-paper-abstracts icon skimlit-nlp-model-for-sentence-classification-in-paper-abstracts

Skimlit: NLP Model for Sentence Classification. Replicates 'Neural Networks for Joint Sentence Classification in Medical Paper Abstracts.' Using PubMed 20k RCT dataset, this project trains a deep learning model to categorize sentences in paper abstracts for efficient literature skimming by researchers.

stereo-disparity-map-generator icon stereo-disparity-map-generator

This code generates a disparity map using the StereoSGBM algorithm. The disparity map represents the difference in pixel coordinates between corresponding points in a pair of stereo images. It provides depth information for each pixel, which can be used for tasks such as 3D reconstruction, object detection, and scene understanding.

stereovision-depthestimation icon stereovision-depthestimation

The StereoVision-DepthEstimation project utilizes computer vision techniques to estimate real-time depth from a webcam. It employs stereo vision and facial feature tracking, providing accurate depth measurements. Explore the world of 3D perception and unlock new possibilities in computer vision.

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