Repository to track Data Analysis done on various datasets available online

A demonstration of exploartory data analysis with hypothesis testing.

A machine learning project that predicts car prices based on a dataset.

Bike Sharing (Rentals) machine learning regression to predict total rentals by considering features of dataset

prediction with regression for salary_hike and delivery time dataset

It's designed to take you on a journey through the fundamental principles and applications of Linear Regression.

This assignment is a programming assignment wherein you have to build a multiple linear regression model for the prediction of demand for shared bikes.

At ferreyros, prioritizing sales opportunities for spare parts and services allows them to provide the best service to customers who need it most. This challenge is to use historical opportunity data to estimate the probability of closing new opportunities.

This github repositiory contains the Flight Price Prediction project aims to develop a machine learning model to predict flight ticket prices based on various factors such as departure and arrival locations, dates, airlines, and other relevant features.

Analysis will help Jamboree in understanding what factors are important in graduate admissions and how these factors are interrelated among themselves. It will also help predict one's chances of admission given the rest of the variables.

The "Advertising Impact Analysis" project aims to analyze the relationship between advertising expenditure across different channels (such as TV, radio, online) and its impact on sales or revenue.

Used cars price prediction using Python, Machine Learning, HTML and CSS.

Utilizing advanced Bidirectional LSTM RNN technology, our project focuses on accurately predicting stock market trends. By analyzing historical data, our system learns intricate patterns to provide insightful forecasts. Investors gain a robust tool for informed decision-making in dynamic market conditions. With a streamlined interface, our solution

This repo hosts an end-to-end machine learning project designed to cover the full lifecycle of a data science initiative. The project encompasses a comprehensive approach including data Ingestion, preprocessing, exploratory data analysis (EDA), feature engineering, model training and evaluation, hyperparameter tuning, and cloud deployment.

Utilizando-se a técnica de regressão linear, com o auxílio dos frameworks scikit-learn e statsmodel, foi possível criar um modelo de predição de preços de imóveis, com base em variáveis explanatórias de um database.

Utilizando-se a técnica de regressão linear, com o auxílio do framework scikit-learn, foram realizados dois projetos nos quais foram utilizados dois databases diferentes (um de consumo de cerveja, e outro do preço de imóveis). Utlizando-se ambos, foi possível prever o consumo de cerveja e o preço dos imóveis, com base nas variáveis explanatórias.

Explore the complete lifecycle of a machine learning project focused on regression. This repository covers data acquisition, preprocessing, and training with Linear Regression, Decision Tree Regression, and Random Forest Regression models. Evaluate and compare models using R2 score. Ideal for learning and implementing regression use cases.

Linear_Regression_Practical_Salary

This machine learning project focused on predicting food delivery times. The code emphasizes essential tasks such as data cleaning, feature engineering, categorical feature encoding, data splitting, and standardization to establish a solid foundation for building a robust predictive model.

Intrusion Detection System for MQTT Enabled IoT.