# A Structured List of 70 Articles That I Wrote About Data Science

--

Help you speed up your learning process.

I have been writing about data science for almost a year now. Since data science is a broad and interdisciplinary field, I did not focus on a specific topic. The articles I have written cover topics related to data analysis and visualization, machine learning, deep learning, statistics, and linear algebra. I have also written many practical guides that cover widely-used data analysis and visualization libraries such as NumPy, Pandas, Matplotlib, Seaborn, and so on.

I have decided to organize these articles so that they will provide a structured introduction for those who want to start a career in data science. I have written over 100 articles but the list below contains 70 articles which I think provide a structured and comprehensive introduction.

The articles are grouped under the following categories:

- Machine Learning Algorithms
- Machine Learning Practical
- General Machine Learning Concepts
- Deep Learning
- Data Analysis (NumPy and Pandas)
- Data Visualization (Matplotlib, Seaborn, Plotly)
- Statistics
- Linear Algebra
- Practical Guides

**Machine Learning Algorithms**

## Supervised

- Logistic Regression — Explained
- Support Vector Machine — Explained
- K-Nearest Neighbors (kNN) — Explained
- Naive Bayes Classifier — Explained
- Decision Trees and Random Forests — Explained
- Gradient Boosted Decision Trees — Explained
- Understanding the LightGBM

## Unsupervised

- DBSCAN Clustering — Explained
- Hierarchical Clustering — Explained
- K-Means Clustering — Explained
- Principal Component Analysis — Explained