Simple-linear-Reg-1

Examples about Data Science Packages

Supervised-ML---Multiple-Linear-Regression---Cars-dataset. Model MPG of a car based on other variables. EDA, Correlation Analysis, Model Building, Model Testing, Model Validation Techniques, Collinearity Problem Check, Residual Analysis, Model Deletion Diagnostics (checking Outliers or Influencers) Two Techniques : 1. Cook's Distance & 2. Levera…

how to perform t-testing & ANOVA

Tuning Trend/ Seasonality/ Error level from Exponential Smoothing model to make futrure forcast

This is my submission to be part of TusDatos

First project implementing Logistic Regression

Оптимизация производственных расходов металлургического комбината ООО «Так закаляем сталь».

Built a linear regression model to predict shared bike demand post-quarantine. Identified key variables affecting revenue and assessed model accuracy in describing bike demand.

Data Science: analytics for health and medicine WHO

The Bike-Sharing Demand Prediction Project aims to develop a predictive model to estimate the demand for shared bikes in the American market for BoomBikes, a bike-sharing provider looking to accelerate revenue post the Covid-19 pandemic. The project involves thorough data exploration and preprocessing.

OpenClassrooms Data Analyst 2022-2023 - Projet 6

Python web application for exploring and forecasting crime rates in NYC

O Statsmodels é uma biblioteca em Python dedicada à estimação e teste de modelos estatísticos. Ele fornece ferramentas para realizar análises estatísticas detalhadas, como regressão linear, modelos de séries temporais, análise de variância e testes estatísticos.

Supervised-ML---Multiple-Linear-Regression---Toyota-Cars. EDA, Correlation Analysis, Model Building, Model Testing, Model Validation Techniques, Collinearity Problem Check, Residual Analysis, Model Deletion Diagnostics (checking Outliers or Influencers) Two Techniques : 1. Cook's Distance & 2. Leverage value, Improving the Model, Model - Re-buil…

Working with consumer data to build a binary logistic machine that predicts the probability of purchasing from the catalog. Training that machine using an estimation sample, then testing and validating the machine using a holdout sample. I also analyze the mailing strategy we should use to achieve profits.

Data Science Project: To build a multiple linear regression model for the prediction of car prices.

Data Science Project: To predict which factors leads to churn and find customers who are likely to churn.