https://github.com/rampal-punia/ml-for-beginners
A comprehensive introduction to Machine Learning (ML) for beginners covering various ML concepts, terminologies, and projects that will help you build a strong foundation in ML.
https://github.com/rampal-punia/ml-for-beginners
machine-image machine-learning machine-learning-algorithms machine-vision machinelearning-python ml ml-project
Last synced: about 2 months ago
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A comprehensive introduction to Machine Learning (ML) for beginners covering various ML concepts, terminologies, and projects that will help you build a strong foundation in ML.
- Host: GitHub
- URL: https://github.com/rampal-punia/ml-for-beginners
- Owner: rampal-punia
- Created: 2023-04-18T05:17:55.000Z (over 2 years ago)
- Default Branch: master
- Last Pushed: 2023-04-18T12:46:37.000Z (over 2 years ago)
- Last Synced: 2025-03-11T01:08:40.802Z (7 months ago)
- Topics: machine-image, machine-learning, machine-learning-algorithms, machine-vision, machinelearning-python, ml, ml-project
- Homepage:
- Size: 172 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Roadmap: roadmap_to_learn_ml.md
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README
# ML For Beginners
This repository is intended for beginners who want to learn about Machine Learning. It contains a collection of ML terminologies and basic ML projects that cover a wide range of topics.
## Table of Contents
- [Introduction](https://github.com/CodingMantras/ml-for-beginners#introduction)
- [Projects](https://github.com/CodingMantras/ml-for-beginners#projects)
- [Terminologies](https://github.com/CodingMantras/ml-for-beginners#terminologies)
- [Contributing](https://github.com/CodingMantras/ml-for-beginners#contributing)
## Introduction
Machine Learning is a rapidly growing field that has many practical applications in various industries. This repository is designed to introduce beginners to the fundamental concepts of Machine Learning.
## Projects
The following projects are included in this repository:
- Titanic data visualization
- MNIST dataset
- Housing property rate
Each project has a detailed explanation of the dataset and the code implementation.
## Terminologies
The following terminologies are included in this repository:
- [Accuracy](https://github.com/CodingMantras/ml-for-beginners/blob/master/precision-recall-accuracy-f1score/accuracy_of_ml_model.md)
- [Precision](https://github.com/CodingMantras/ml-for-beginners/blob/master/precision-recall-accuracy-f1score/precision_of_ml_model.md)
- [Recall](https://github.com/CodingMantras/ml-for-beginners/blob/master/precision-recall-accuracy-f1score/recall_of_an_ml_model.md)
- [F1 Score](https://github.com/CodingMantras/ml-for-beginners/blob/master/precision-recall-accuracy-f1score/f1_score_of_ml_model.md)
- [True Positive & True Negative](https://github.com/CodingMantras/ml-for-beginners/blob/master/true_positive_true_negative.md)
- [Confusion Matrix]()
- [Overfitting]()
- [Underfitting]()
- [Gradient Descent]()
Each terminology has a detailed explanation and code snippets for implementation.
## Contributing
Contributions are welcome! If you have any ML projects or terminologies that you would like to share, feel free to contribute to this repository by submitting a pull request.