ML algorithms in Python
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Updated
Jun 23, 2022 - Jupyter Notebook
ML algorithms in Python
2nd Year: 1st - 92. A brief project and report on using the OULAD data set to predict and return a CSV of students final grades, from a variety of features, using a Random Forest or an SVC.
Driver codes in C for RTOS development on STM32F411VETx
Performed Sentiment Analysis on the Twitter Us Airline dataset
ECE NTUA Neural Networks
Revolutionize customer feedback analysis with our NLP Insights Analyzer. Utilize cutting-edge text preprocessing to transform raw reviews into a machine-friendly format. Explore sentiment models, such as Logistic Regression and Naive Bayes, employing cross-validation for model robustness.
Machine Learning - Classification
Classification Models
Implement an algorithm that can classify handwritten digits, based on MNIST database.
analyzing data, performing visualization, and training five different machine learning models, including two ensemble models
Detecting Fake Job Postings - Data Visualization, TF-IDF, XGBoost, SVC
Created a vehicle detection and tracking pipeline with OpenCV, histogram of oriented gradients (HOG), and support vector machines (SVM). Optimized and evaluated the model on video data from a automotive camera taken during highway driving.
Projet réalisé dans le cadre de l'UV SY32 et ayant pour objectif d'établir un modèle capable de reconnaître la position de visages sur une image
Twitter US Airline Sentiment Analysis
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