AI & Machine Learning: Detection and Classification of Network Traffic Anomalies based on IoT23 Dataset
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Updated
Jul 30, 2021 - Python
AI & Machine Learning: Detection and Classification of Network Traffic Anomalies based on IoT23 Dataset
First Assignment in 'NLP - Natural Languages Processing' course by Prof. Yoav Goldberg, Prof. Ido Dagan and Prof. Reut Tsarfaty at Bar-Ilan University
From scratch implementations of some algorithms in Machine Learning SkLearn style in Python
Multiclass logistic regression implementation from scratch
a vectorized binary logistic regression implementation in python.
Personal Project 2: using machine learning algorithms to predict the existence of heart disease based on a numerical and categorical dataset.
Implementation of Logistic Regression and MLP binary classifiers from scratch.
Logistic Regression Classifier; MVC Classifier; Logistic regression Classifier with Squared x parameters
🧪 Classifies toxic comments (EN + RU) using TF-IDF and logistic regression.
Basic code for training the Classification model like Logistics Regression using some data encoding or exploration techniques.
Sentiment Analyzer built with Python. Pre-processed data and built a basic Bag-of-words model. Implemented the Naive Bayes, Decision Tree, and Logistic Regression classifiers. Also ran classifiers on a dataset of Yelp reviews for extra credit. Completed for school.
GLOBAL_HEALTH_ANALYSIS is a comprehensive tool designed to evaluate health trends across different regions. It uses data visualization to highlight key health indicators, enabling users to identify areas needing attention.
Music classifier for first mandatory assignment in FYS-2021
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