## The Algorithms of Artificial Intelligent

I'm new to Python programming and - actually - it just was started in the middle of 2020 for a specific corporate purpose where I'd worked at. So, I've been learned for couple months to explore what is what about Python, and - since there's no best fit guidance about machine learning methodologies - here I summarized about 17 common algorithms I found.**A. Supervised Learning**

Split into 2 methods:

- Regression
- Linear
- Logistic
- Polynomial
- Classification
- K-Nearest Neighbors (KNN)
- Decision Tree (DT)
- Naive Bayes (NB)
- Support Vector Machine (SVM)

**B. Unsupervised Learning **

Split into 3 methods with 2 models (ML & DL):

- Machine Learning

- Clustering
- K-Means
- Hierarchical Clustering
- T-SNE Clustering
- DBScan
- Dimension Reduction
- Principal Component Analysis
- Anomaly Detection
- Auto-Encoder
- Hebbian Learning

- Deep Learning
- Generative Models
- Generative Adversarial Network
- Self Organizing Maps

I wrapped this post on a video I published in Youtube:

Thank you for your reading & subs. I'll update this post as soon as I found any of new algorithms.

Labels: Programming, Python