End-to-End DataScience Casestudy
The main aim of the project is to analyze data to summarize their main characteristics with visual methods and to predict the price using Machine Learning Model.
In this project we have made exploratory data analytics on uber dataset and came to know the effect of each field on price with every other field of the dataset. Then we apply different machine learning models to complete the analysis,Then the best performing model was suggested for further predictions of the label ‘Price’.
The analysis is broken up into 3 sections:
- Data Loading and Preparation.
- Exploration and visualization
- Prediction.
- Python
- numpy
- Pandas
- Matplotlib
- Scipy
- seaborn
https://www.kaggle.com/fivethirtyeight/uber-pickups-in-new-york-city
This project analyzes multiple attributes related to Uber cabs that allows to get better insights regarding the functioning of the multi national cab company and We have used machine learning algorithms to predict the price of Uber, so that it is easy for the company to do analysis on price based on certain features.