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Extensive Collection of Jupyter Notebooks focused on Machine Learning covering different techniques includes Feature Engineering, Feature Selection, Feature Extraction, Model Training & Testing.

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satyamgupta53/machine-learning-notebooks

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Machine Learning

This repository is your one-stop shop for exploring different machine learning techniques in different scenarios. We delve into the world of machine learning to tackle the challenge of creating sustainable working high-accuracy models.

This repository provides all the tools you need to get started, including:

  • Code for data preparation and model training
  • Feature Selection & Engineering Techniques
  • Feature Extraction & PCA techniques
  • Classification, Regression & Clustering Models

Whether you're a seasoned pro or a curious beginner, feel free to dive in, experiment with the code, and contribute to the model's growth!

Installation

Use the package manager pip to install any of the required libraries in your computer system.

pip install _______

Usage

pip install pandas
import pandas as pd

# read a csv file
data = pd.read_csv(file_path, sep=",")

# print top 5 rows
data.head()

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

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Extensive Collection of Jupyter Notebooks focused on Machine Learning covering different techniques includes Feature Engineering, Feature Selection, Feature Extraction, Model Training & Testing.

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