https://github.com/neemiasbsilva/machine-learning-algorithm
Some algorithms of machine learning like Regression, Cluster, Deep Learning, and much more.
https://github.com/neemiasbsilva/machine-learning-algorithm
algorithms headbrain-dataset jupyter-notebook linear-regression logistic-regression machine-learning machine-learning-tutorials pca-titanic-dataset python python3 random-forest-mnist titanic-dataset unsupervised-learning wine-quality xor-neural-network
Last synced: 9 months ago
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Some algorithms of machine learning like Regression, Cluster, Deep Learning, and much more.
- Host: GitHub
- URL: https://github.com/neemiasbsilva/machine-learning-algorithm
- Owner: neemiasbsilva
- License: mit
- Created: 2019-09-21T04:02:02.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2022-11-20T11:21:14.000Z (about 3 years ago)
- Last Synced: 2025-03-25T15:14:18.844Z (9 months ago)
- Topics: algorithms, headbrain-dataset, jupyter-notebook, linear-regression, logistic-regression, machine-learning, machine-learning-tutorials, pca-titanic-dataset, python, python3, random-forest-mnist, titanic-dataset, unsupervised-learning, wine-quality, xor-neural-network
- Language: Jupyter Notebook
- Homepage:
- Size: 12.2 MB
- Stars: 10
- Watchers: 2
- Forks: 4
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
- License: LICENSE
Awesome Lists containing this project
README
[![Scikit Learn][scikit-learn-shield]][scikit-learn-url]
[![TensorFlow][tensorflow-shield]][tensorflow-url]
[![Keras][keras-shield]][keras-url]
[![MIT License][license-shield]][license-url]
# Machine Learning Algorithms
###### "Google’s self-driving cars and robots get a lot of press, but the company’s real future is in machine learning, the technology that enables computers to get smarter and more personal" - Eric Schmidt (Google Chairman)
This repository was created for shown some algorithms of machine learning. It's important you have a High-Level Python to understanding of various machine learning algorithms. These should be sufficient to get your hands dirty.
## Description About this Repository
Basically this repository is defined in two folder. The folder represents the subarea of machine learning that is supervised learning, and unsupervised learning.
Bellow, I describe the files of the each folder, in other wold the supervised and unsupervised learning algorithm's.
### Supervised Learning:
-
Linear Regression; -
Logistic Regression; -
Logistic Regression applied to Cat Dataset ; -
Random Forest applied to Mnist Dataset; -
XOR gates Using NN; -
Neural Network applied to Cat Dataset ; -
Deep Learning Apply to Titanic Dataset.
### Unsupervised Learning:
## Life Cycle of Machine Learning
For all these techniques, the following order was maintained:
1. Collecting Data
2. Analysis Data
3. Data Wrabling
4. Test & Train
5. Accuracy Check
## Getting Started
### Prerequisites
What things you need to undertand this repository
```
Good knowledgment in Machine Learning, Deep Learning, Computer Vision and know how to use jupyter-notebook.
```
### Usage
To use some algorithms, like Deep Learning applied to coin brazillians, you need a good computer system with GPU (Graphic Processing Unit).
#
Sincerely: Neemias B. Silva
[license-shield]: https://img.shields.io/github/license/Ileriayo/markdown-badges?style=for-the-badge
[license-url]: https://github.com/neemiasbsilva/mlops-with-tensorflow-extends/blob/main/LICENSE.txt
[tensorflow-shield]: https://img.shields.io/badge/TensorFlow-%23FF6F00.svg?style=for-the-badge&logo=TensorFlow&logoColor=white
[tensorflow-url]: http://tensorflow.org/
[keras-shield]: https://img.shields.io/badge/Keras-%23D00000.svg?style=for-the-badge&logo=Keras&logoColor=white
[keras-url]: https://www.tensorflow.org/guide/keras?hl=pt-br
[scikit-learn-shield]: https://img.shields.io/badge/scikit--learn-%23F7931E.svg?style=for-the-badge&logo=scikit-learn&logoColor=white
[scikit-learn-url]: https://scikit-learn.org/stable/
[tfx-libraries]: reports/figures/tfx-components.png