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

Help you speed up your learning process.

Photo by Fitore F on Unsplash

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

Machine Learning — Practical

• Machine Learning Made Easy by PyCaret