https://github.com/codeperfectplus/hands-on-machine-learning-with-scikit-learn-tensorflow-and-keras
Implementing different aspects of Machine learning in this Repository. Contributions are welcome
https://github.com/codeperfectplus/hands-on-machine-learning-with-scikit-learn-tensorflow-and-keras
data-analysis feature-engineering feature-selection hacktoberfest machine-learning missing-value-treatment python3 scikit-learn tensorflow
Last synced: 11 months ago
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Implementing different aspects of Machine learning in this Repository. Contributions are welcome
- Host: GitHub
- URL: https://github.com/codeperfectplus/hands-on-machine-learning-with-scikit-learn-tensorflow-and-keras
- Owner: codeperfectplus
- License: mit
- Created: 2020-09-27T07:42:43.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2022-10-22T05:46:56.000Z (over 3 years ago)
- Last Synced: 2024-05-02T04:12:21.916Z (almost 2 years ago)
- Topics: data-analysis, feature-engineering, feature-selection, hacktoberfest, machine-learning, missing-value-treatment, python3, scikit-learn, tensorflow
- Language: Jupyter Notebook
- Homepage:
- Size: 3.13 MB
- Stars: 3
- Watchers: 1
- Forks: 3
- Open Issues: 1
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Hands on Machine Learning with Scikit-Learn, Tensorflow and Keras
Implementing differnt aspects of Machine learning in this Repository. Contributions are welcome
## Features selection
**Feature selection** – also known as **variable selection**, **attribute selection**, or
**variable subset selection** – is a method used to select a subset of features (variables,
dimensions) from an initial dataset.
Feature selection is a key step in the process of building machine learning models and
can have a huge impact on the performance of a model. Using correct and relevant features as
the input to your model can also reduce the chance of overfitting, because having more relevant
features reduces the opportunity of a model to use noisy features that don't add signal as input.
Lastly, having less input features decreases the amount of time that it will take to train a
model.