AI & Machine Learning: Detection and Classification of Network Traffic Anomalies based on IoT23 Dataset

Assumptions of Logistic Regression, Clearly Explained

Recognition of Persomnality Types from Facebook status using Machine Learning

To predict the the Prostate cancer is Benign or Malignant

Neural networks is a model inspired by how the brain works. It is widely used today in many applications: when your phone interprets and understand your voice commands, it is likely that a neural network is helping to understand your speech; when you cash a check, the machines that automatically read the digits also use neural networks.

Build and evaluate various machine learning classification models using Python.

Loan Prediction using Classification Techniques

Classification Modeling: Probability of Default

Logistic regression and dynamic feature selection based android malware detection approach

This project involves predicting wine quality using logistic regression in Jupyter Notebook. Wine quality prediction is an important task in the field of wine production and quality control, as it helps assess the overall quality of wines based on various chemical properties.

LDA(Linear Discriminant Analysis) for Seed Dataset

First Assignment in 'NLP - Natural Languages Processing' course by Prof. Yoav Goldberg, Prof. Ido Dagan and Prof. Reut Tsarfaty at Bar-Ilan University

Credit card Fraud Detection using AutoEncoders Neural network to encode complete dataset. Training the Genuine Transaction Data alone and create Anomaly Detecting Classification Model using the simple Logistic Regression Classifier and XGBoost to predict the Fraud transaction from the Encoded dataset.

CS289A | Supervised ML on MBTI types

Development and comparison of 12 machine learning models to predict autism as well as a discussion of the process.

Customer Churn Prediction using Machine Learning

This repository contains a research paper and its details done by Tisha Jillian and Tara Nirmala Kusuma as an AoL (Assurance of Learning) for COMP6696001 - Research Methodology in Computer Science Course.

Training of ML models with CIC dataset of malicious DoH traffic