YassirMatrane

AI-checkpoints

AICourse

Une formation AI

arabicTextClassification

After collecting 40 thousand tweets and preprocessing it, I used word embeddings with arabert and tf-idf along with two neural network architectures and 5 machine learning algorithms. Due to the huge size of the dataset, I chose Amazon SageMaker to train the models

carPricePrediction

checkpoint-1

DealingWithImbalancedData

This project aims to show you the different strategies to mitigate the imbalanced data issue by combining different approaches to resampling data (undersampling, oversampling, and hybrid sampling) and different machine learning algorithms and visualizing the results in order to choose the performest approaches. I highly recommend reading the ppt file to understand better and have an idea about the newest approaches.

EnforcingSocialDistancingThroughComputerVision

This tool has four features, which are detecting humans in the frame using deep learning algorithms (faster-rcnn and yolo), calculating the distance between every human who is detected in the frame (scale factor and homography), showing how many people are at high, low and not at risk and generating notifications to warn if anyone is found violating laws.

featureEngeneeringModules

Instead of hand-coding the preprocessing of data within a data science life cycle project, you can make use of these modules to automatically preprocess your data

flaskTPsTeaching

formation-python-5

YassirMatrane/arabicTextClassification

After collecting 40 thousand tweets and preprocessing it, I used word embeddings with arabert and tf-idf along with two neural network architectures and 5 machine learning algorithms. Due to the huge size of the dataset, I chose Amazon SageMaker to train the models

YassirMatrane/DealingWithImbalancedData

This project aims to show you the different strategies to mitigate the imbalanced data issue by combining different approaches to resampling data (undersampling, oversampling, and hybrid sampling) and different machine learning algorithms and visualizing the results in order to choose the performest approaches. I highly recommend reading the ppt file to understand better and have an idea about the newest approaches.

YassirMatrane/EnforcingSocialDistancingThroughComputerVision

This tool has four features, which are detecting humans in the frame using deep learning algorithms (faster-rcnn and yolo), calculating the distance between every human who is detected in the frame (scale factor and homography), showing how many people are at high, low and not at risk and generating notifications to warn if anyone is found violating laws.

YassirMatrane/AI-checkpoints

YassirMatrane/AICourse

Une formation AI

YassirMatrane/carPricePrediction

YassirMatrane/checkpoint-1

YassirMatrane/featureEngeneeringModules

Instead of hand-coding the preprocessing of data within a data science life cycle project, you can make use of these modules to automatically preprocess your data

YassirMatrane/flaskTPsTeaching

YassirMatrane/formation-python-5

YassirMatrane/helloWorldTeaching

YassirMatrane/phdProject

YassirMatrane/python-formation

YassirMatrane/python-scrapping

YassirMatrane/pythonCourseTeaching

YassirMatrane/scrappingTPsTeaching

YassirMatrane/slr_phd

YassirMatrane/tripAdvisor-restaurants

TripAdvisor-restaurants is a data mining project wherein we performed data preprocessing and analysis to explore the best restaurants via visualization and machine learning algorithms