Manaliagarwal/Walmart-Sales-Forcasting

A regression based modeling project to forecast the sales of Walmart

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Abhishek20182/Analyze-AB-Test-Results

Udacity Data Analyst Nanodegree - Project III

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rochitasundar/Regression-dynamic-price-prediction-ReCell

The objective is to build a ML-based solution (linear regression model) to develop a dynamic pricing strategy for used and refurbished smartphones, identifying factors that significantly influence it.

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ozgurkalan/stats4ML

My notes in Jupyter Notebooks for statistics, probability, and plotting applied with major python libraries as an introduction to machine learning.

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mstftmk/K132-Data-Science-Bootcamp

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Usama-Tariq/-Udacity_Analyze-A-B-Test-Results_Project-3_DAND

A/B tests are very commonly performed by data analysts and data scientists. It is important that you get some practice working with the difficulties of these.

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Siddhant-Ray/TimeSeries-ARIMA

An implementation of an ARIMA time series forecast using Python statsmodels and scipy.

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akhilpatlolla/Random-Good-Data-Science-Stuff

Random Good Data Science Stuff

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KizMan-23/time_series-analysis

Time-Based Analysis projects using pandas, scikit-learn and statsmodel.tsa

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HamzA-1729/PredictifyGPA-MLR

Multiple Linear Regression that predicts the GPA of students using OLS.

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adrianc7/key-indicators-life-expectancy

This project analyzes key socioeconomic and health indicators influencing life expectancy in developing countries, using regression models and statistical techniques to derive actionable insights from WHO and UN datasets.

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HamzA-1729/PredictifyGPA-SLR

Simple Linear Regression that predicts the GPA based of students using OLS.

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arnabberawork/BoomBikesSharingCaseStudy

Upgrad and IIITB Assignment - Linear Regression model for a US bike-sharing provider BoomBikes

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shwetapardhi/Assignment-04-Simple-Linear-Regression-1

Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Model Predictions using simple linear regressi

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dpassos91/milesinthesky_project3

Data Science: Storytelling and Deployment - analyzing LEGO Database with Streamlit.

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brprojects/MLS_model

In this project I predict the 2016 MLS season using historical data and Poisson regression. The project includes cleaning, preprocessing and analyzing the dataset, building and evaluating predictive models for match outcomes, forecasting team performance and simulating the league table. It uses Pandas, Numpy, MatPlotLib and StatsModel libraries.

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Manalelaidouni/MLR-Ames

MLR Statistical Analysis and Prediction of Ames Real Estate Prices with Streamlit

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DiegoConce/CrimeAnalysis-HumanDataScience

Human Data Science Course Project A.Y. 2022/2023 @ Alma Mater Studiorum University of Bologna - UNIBO

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hmulagund/Assignment_04_Simple_Linear_Regression-1

Assignment-04-Simple-Linear-Regression-1 Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Model Predictions using simple linear regression.

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deepakrameshgowda/Lead-Scoring-Logistic-model

Model to identify the potential lead by assigning a score for their rate of conversion. Therefore, reaching out to potential is no more a brainstorming task.

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nitinjosephrepo/Analyzing-Online-Shopper-Purchase-Intention

Analyze online shoppers' purchase intentions using Logistic Regression, K-means clustering & A/B Testing

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Elliott-dev/NYC_Bike_Counts_Retrospective_Analysis

I perform a retrospective analysis on the linear regression analysis that I previously performed on the NYC Bike Counts dataset. Specifically, I analyze my linear regression analysis to identify anything that I could have done differently.

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Elliott-dev/NYC_Bike_Linear_Regression-

I used the New York Bike Counts dataset to formulate a hypothesis about the number of bikes crossing the Brooklyn Bridge. This dataset contains the number of bikes that crossed each bridge during each day. I first used this dataset to formulate a hypothesis and then used linear regression to test if my hypothesis was correct.

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Smcgb/Udacity_Statistics

This dataset provided by Udacity in their data analyst course proivdes a walkthrough of an AB test for customer conversion.

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Saad-Hussain31/Defaulter-Classification

I am interested in predicting whether an individual will default on his or her credit card payment, on the basis of annual income and monthly credit card balance. First I will use Logistic regression with 1 feature only (balance) and then multiple logistic regression with 2 features (balance and income).

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sednabcn/Python-ML-Statsmodels

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

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jpadillo/Analyze-AB-Test-Results

A data analytics project that utilizes PANDAS, Numpy, Matplotlib and statsmodel to analyze the results of hypothesis testing and regression modeling in determining whether a website update should be launched.

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itsfk/Python-for-Time-Series-Data-Analysis

Time Series Analysis

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shashankvmaiya/Boston-Housing-Price-Prediction

House price prediction using Linear Regression models (scikit learn and statsmodel)

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