Simple-linear-Reg-1
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Updated
Oct 4, 2020 - Jupyter Notebook
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.
Analysing Time series and spatiotemporal data
Currency Exchange Rate Forecasting is a Time-Series forecasting model which is built to forecast the INR-USD Currency Exchange Rates using SARIMAX algorithm.
Data Science Project: To build a multiple linear regression model for the prediction of car prices.
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