ft_linear_regression
Data Science: Linear Regression
Really hope I ACTUALLY finish this project :(. I did it! :)
Don't really know what I'm doing with this one but the plan is to accelerate my data science learning using the ft_linear_regression and hopefully the DSLR (Datascience X Logistic Regression) modules at 42. Found one other person doing the project on github. This is the first project in the deep learning branch at 42.
Linear Regression
- Linear Regression is a topic in statistics that is used as a predictive analysis tool.
- It aims to form relationships between data points and:
- determining the strength of predictors,
- forecasting an effect,
- trend forecasting.
Objective
This project aims to predict the price of a car based on it's mileage.
Topics covered
- Statistics
- Predictive Analysis
- Regression Modelling
Python Dependencies
pandas,plotly,math,tqdm(for progress bar in terminal)
Usage
- Start the trainer. Run
python .\trainer.py .\dataset_00.csv, where.\dataset_00.csvis the training dataset in csv format:
| mileage | price |
|---|---|
| 240000 | 3650 |
| 139800 | 3800 |
| 150500 | 4400 |
- Start the predictor. Run
python .\predictor.py <SAMPLE_MILEAGE>, where<SAMPLE_MILEAGE>is the mileage is a number (unsigned).
Result
This is a sample data set where learning rate = 0.5, iterations = 200
Resources
DataSci, My repo for all python and data science learning