（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

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.

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.

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.

Expresso Churn Prediction Challenge - dealing with imbalanced dataset

This repository contains introductory notebooks for Naive bayes algorithm

‘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.

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

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

Predicts the qualified employee for promotion using Classification

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

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

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

Classifying iris flower dataset by using Naive Bayes classifier

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

classifying employee attrition

The Titanic dataset includes passenger information such as survival status, ticket class, gender, age, family relations aboard, fare, cabin, and port of embarkation. It's widely used for predictive modeling to understand survival patterns based on passenger attributes.

Naive Bayes (From Scratch)

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.