This repository is a collection of various machine learning algorithms implemented in Python. From basic algorithms to more advanced ones, this repository aims to serve as a comprehensive guide and resource for anyone looking to delve into the world of machine learning.
Machine learning (ML) is a subset of artificial intelligence that involves teaching computers to learn from data, rather than being explicitly programmed. It operates by constructing algorithms that, after being exposed to training data, can make predictions or decisions without direct human intervention. Initially, ML tackled simple problems, like sorting data or recognizing patterns in numbers. However, its early applications were predominantly in domains such as handwriting recognition or basic game playing.
Fast forward to today, and ML has permeated nearly every sector. In the real world, it drives advancements in areas ranging from healthcare, where algorithms can detect diseases, to finance, optimizing stock market trading strategies. While its early days saw solutions for narrower tasks, modern ML, especially with the rise of deep learning, addresses complex challenges: translating languages in real-time, driving autonomous vehicles, generating art, and even aiding in cutting-edge scientific research.
- 01 - Minimum Distance Classifier - Notebook
- 02 - K-Means Clustering - Notebook
- 03 - K Neighbors Classifier (KNN) - Notebook
- 04 - Decision Tree Classifier - Notebook
- 05 - Principal Component Analysis (PCA) - Notebook
- 06 - Support Vector Machine (SVM) - Notebook
- 07 - Simple and Multilayer Perceptron (MLP) - Notebook
- 08 - FeedForward Neural Network (FFNN) and Recurrent Neural Network (RNN) - Notebook
- ... (continue for all algorithms)
To use these notebooks:
- Clone the repository:
git clone https://github.com/MiguelAngel-ht/Machine_Learning_Algorithms-2021/tree/main
- Navigate to the repository directory and install any necessary libraries/packages.
- Open the desired notebook using your preferred notebook viewer/editor, such as Jupyter Notebook.
- Follow the instructions within each notebook.
This repository is licensed under the MIT License - see the LICENSE file for details.