Helps to work with projects repositories and SVC operations.

ML algorithms in Python

Driver codes in C for RTOS development on STM32F411VETx

SVM

Performed Sentiment Analysis on the Twitter Us Airline dataset

Analysis of Support Vector Machine

ECE NTUA Neural Networks

Run UI Process from Win Service

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

Predicts gender of a name based on name metadata

Crime Category Prediction by Description. This is sample of multiple class Text Classification with Scikit-Learn.

In this project I used different classification algorithms to find out fatal health. I used Kaggles free GPUs and Datasets in this competion. Those different algorithms include random forrest, decision tree, xgboost and so on. Initially I used feature engineering to get my data into the best shape