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 is a topic in statistics that is used as a predictive analysis tool.
• It aims to form relationships between data points and:

1. determining the strength of predictors,
2. forecasting an effect,
3. trend forecasting.

This project aims to predict the price of a car based on it's mileage.

• Statistics
• Predictive Analysis
• Regression Modelling

• pandas, plotly, math,
• tqdm (for progress bar in terminal)

1. Start the trainer. Run python .\trainer.py .\dataset_00.csv, where .\dataset_00.csv is the training dataset in csv format:

2. Start the predictor. Run python .\predictor.py <SAMPLE_MILEAGE>, where <SAMPLE_MILEAGE> is the mileage is a number (unsigned).

This is a sample data set where learning rate = 0.5, iterations = 200

DataSci, My repo for all python and data science learning