Traffic Accident Analysis using python machine learning

This is a very Important part of Data Science Case Study because Detecting Frauds and Analyzing their Behaviours and finding reasons behind them is one of the prime responsibilities of a Data Scientist. This is the Branch which comes under Anamoly Detection.

Our goal was to create a ML bot that analyzes real time trading data to determine the most opportune times buy and sell stock

Utilizing machine learning to examine deforestation rates in the undeveloped region of Paraguay's Chaco

Imbalanced Intent classification model with deployment

Course Project for CS273A: Machine Learning at UCI

The aim of this project is to predict fraudulent credit card transactions with the help of different machine learning models.

Case study from UDACITY Data Scientist Nanodegree

Corporate Credit Rating Prediction System - Knowledge Engineering Project - A.A. 2023-2024

Machine learning is used to analyze and predict attrition flags in credit card customers.

Facial skin disease detection using Neural Networks

Data Science Classification General Notebook

Prediction module for Tumor Teller - primary tumor prediction system

Machine Learning analysis for an imbalanced dataset. Developed as final project for the course "Machine Learning and Intelligent Systems" at Eurecom, Sophia Antipolis

An analysis on credit risk

Successfully trained a machine learning model which can predict whether a given transaction is fraud or not.

This repository contain my final projekt on the Data science Skillbox school on the topic: "Development of a machine learning algorithm to predict the behavior of customers of the "SberAvtopodpiska"

Parkinson’s disease is a progressive disorder that affects the nervous system and the parts of the body controlled by the nerves. Symptoms are also not that sound to be noticeable. Signs of stiffening, tremors, and slowing of movements may be signs of Parkinson’s disease.

This project aims to develop a machine learning model to classify SMS messages as spam or not spam. The project encompasses the entire pipeline from data collection and preprocessing to model training, evaluation, and deployment using Streamlit for an interactive user interface.