（陆续更新）重新整理过的基于机器学习的股票价格预测算法，里面包含了基本的回测系统以及各种不同的机器学习算法的股票价格预测，包含：LSTM算法、Prophet算法、AutoARIMA、朴素贝叶斯、SVM、随机森林等

SVM, Logistic Regression, K-Nearest Neighbors Classifier, GaussianNB, Random Forest, XGBoost, DecisionTree Classifier, Ensembled Classifier, ExtraTrees Classifier, Voting Classifier

A Flask web app which predicts whether it will rain tomorrow or not.

Heart disease describes a range of conditions that affect your heart. Diseases under the heart disease umbrella include blood vessel diseases, such as coronary artery disease, heart rhythm problems (arrhythmia), and heart defects you’re born with (congenital heart defects), among others.

Credit-Card-Fraud-Detection project is a binary classification project which predicts the Fraud by using the different classification algorithms

Predicting house prices can help determine the selling price of a house in a particular region and can help people find the right time to buy a home.

Heart disease describes a range of conditions that affect your heart. Diseases under the heart disease umbrella include blood vessel diseases, such as coronary artery disease, heart rhythm problems (arrhythmia), and heart defects you’re born with (congenital heart defects), among others.

Expresso Churn Prediction Challenge - dealing with imbalanced dataset

A powerful stacked ensemble model for income prediction, combining GradientBoosting, AdaBoost, Bagging, Linear Regression, and Decision Trees. Achieves an impressive R² of 0.8761 on the RoS_sample_submission dataset.

‘Buy Now, Pay Later’ (BNPL) is a type of short-term financing used by start-ups like Slice, ZestMoney, Simpl, LazyPay, and Uni, are lowering the bars while approving applications. Building models to detect such customers beforehand.

Bank Marketing Classifcation machine learning using 6 Models each of models given another accuracy

Gain a complete and accurate understanding of the disease you’re dealing with.

The aim is to create a classifier that indicates whether a requested transaction is genuine or fraudulent.

This repository contains introductory notebooks for Naive bayes algorithm

Projeto de MLops com MLflow

UNI S6: K medoids, Gaussian naive bayes & dbscan on SORLIE dataset

Predicts the qualified employee for promotion using Classification

This project is done during the data science T5 bootcamp. Using HR dataset and applying machine learning classification algorithms to predict eligible employees for promotions. Hence save time and effort and expedite the process of promotions in the company.

This repository contains my work for Summer Analytics '22 conducted by IIT Guwahati

Final practical work of the Machine Learning Course with Python dictated by the UTN.

Performance Comparison of Three Classifiers for the Classification of Breast Cancer Dataset

RT_IoT2022 dataset to build an anomaly detection model with K-Means clustering, Naïve Bayes classification, and performance evaluation.

This project implements a Lung Cancer Classification system by integrating the Snowflake Cloud Data Warehouse with Machine Learning. Patient data is fetched directly from Snowflake, preprocessed, and classified using the Naive Bayes (GaussianNB) algorithm.

Bank-Marketing dataset using Mlflow

In this project, Naive Bayes and Logistic Regression models are used to develop a text classification system for Turkish news articles.

This project uses machine learning to build a predictive model that determines what passengers on the Titanic were more likely to survive using passenger data (age, gender, socio-economic class).

🧠 DMAD - Differential Morphing Attack Detection. A project for Fundamentals of Computer Vision and Biometrics course at the University of Salerno.

Classifying iris flower dataset by using Naive Bayes classifier

Naive Bayes (From Scratch)

Titanic Surivial Analysis And Prediction using different machine learning algorithms.