In this project, you’ll help a bike rental company enhance its fleet management and pricing strategy by building a daily bike rental forecasting model using time series analysis techniques in R. Your objectives include loading, cleaning, processing, and analyzing daily rental transaction data, and developing and evaluating time series models for the most accurate predictions.

Forecast bikeshare demand using time series models in R
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Forecast bikeshare demand using time series models in R
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Recommended experience
Objectives
Describe data to answer key questions to uncover insights
Fit well-validated time series models for forecasting future rental bikes demands
Provide analytic insights and data-driven recommendations
Skills you'll demonstrate
- Tidyverse (R Package)
- Rmarkdown
- Data Manipulation
- Time Series Analysis and Forecasting
- Data Visualization
- Data Analysis
- Business Strategy
- R (Software)
- Machine Learning
- Demand Planning
- R Programming
- Interactive Data Visualization
- Model Evaluation
- Trend Analysis
- Data-Driven Decision-Making
- Data Preprocessing
- Forecasting
- Data Cleansing
- Predictive Modeling
Details to know
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About this Project
Project plan
This project requires you to independently complete the following steps:
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Load and explore the data
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Create interactive time series plots
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Smooth time series data
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Decompose and assess the stationarity of time series data
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Fit and forecast time series data using ARIMA models
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