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Taxis-prediction-in-NYC

CASA06 DSSS Coursework

This document is a abstract of the coursework for CASA06 (Data Science of Spatical Science).

Requirement

Deadline: 04/24/2023
Submission: Jupyter notebook
Word Count: Maximum 2000 words
Task:
Select any open dataset relating to an urban or spatial system of your choice and conduct an advanced analysis of the dataset. A complete data analysis process should be undertaken – this will include data validation and cleaning, a data pre-processing phase (e.g. text, image, clustering analysis), and comprehensive analysis (including relevant visualisations) of the data, identifying important trends and insights contained within the dataset.
Mark sheet:
• Analysis and interpretation of data – 70%
- Analysis context and aims (incl. reference to relevant literature and projects)
- Data collection, handling, cleaning and management
- Depth and scope of data analysis
- Appropriateness of data visualisation
- Interpretation and reporting of analysis and major findings
- Clarity of presentation of results
• Demonstration of technical skills – 20%
- Choice and rationale of data analysis methods used
• Creativity of analytical work – 10%
Structure:
• Introduction
• Literature review
• Research question
• Presentation of data
• Methodology
• Results
• Discussion
• Conclusion

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Predict the spatial pattern of taxi in NYC using RF&LSTM

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