Use NLP & Sentiment analysis in Python to determine the impact sentiment has on the price of Bitcoin

This is machine learning loan status classifier web application design & developed using Python HTML CSS JavaScript

multivariate CTG dataset of 2126 pregnant women obtained from University of California Irvine Machine Learning Repository

Using R Language to predict whether a user will download an app after clicking a mobile app advertisement. Click on the link below to see more details!

A deep learning, image classifying project for flower species using PyTorch and Jupyter Notebooks

Hadoop & Spark Machine Learning

Script for Human Activity detection that is based on Kaggle's Human Activity Recognition Dataset Using different methods

Mini-Project for the Data Warehousing and Data Mining lab at MIT, Manipal

Perform two distinct simple trading strategies with various classification models in Python. Generate 'buy' and 'sell' signals based on feature variables for the MSFT security. Signals are selected as the target/label variable used by classifiers.

Análises de Predições de Vendas e Predições de Subscrições de Serviço. A base Retail foi utilizada nos modelos de regressão para previsão de vendas e a base marketing foi utilizada no modelo de classificação para previsão de subscrições do serviço. No trabalho como um todo foram utilizados os modelos de Regressão Linear e Logística, Árvore de De…

EDA and Logistic Regression on demographic factors influence patient appointment booking

Using Python, I explored and engineered data from Enron email metadata and financials, building and tuning a number of scikit-learn classification models to detect persons of interest.

Predicting MLB game winners based on past performance

This repository describes the implementation of Machine Learning techinques using the Statsmodels pacakge

Developed multiple data sets using Classification and Regression techniques to find My Airbnb NY housing price project uses given feature variables to predict housing price. I also compare my predictions to the given target variable, which is the housing price, to check if my prediction fits with the actual price.

Model klasyfikacyjny wykorzystujący algorytm Random Forest napisany w języku R.

It gives the information about the top 5 best and worst performing crops and predicts the price of a particular crop over a period of 6 months. It also has a feature in which you provide the report of soil like nitrogen and PH level and it will suggest you a crop to grow in your farm.

🩺 Powered by Machine Learning algorithms, web-app to help find early stage diabetes prediction.

This is a machine learning-powered web application built with Python, Flask, and SHAP, designed to screen for Depression, Anxiety, and Stress using the standardized DASS-42 questionnaire. It provides explainable AI (XAI) outputs, user history, interactive plots, and bilingual (English/Sinhala) support.