A collection of 100 Data Science Notebooks on different topics.

A genre defines the field in which a problem exists.
| G | E | N | R | E |
|---|---|---|---|---|
| Aerospace | Agriculture | Astronomy | Banking | Customer relations |
| Cyber security | E-Commerce | Education | Entertainment | Finance |
| Food and Lifestyle | Healthcare | Human Resouces | IT & Media | Industries |
| Logistic | Nature | Oil, Minerals & Energy | Art and Craft | Public Safety |
| Sales & Marketing | Science & Tech | Sports & Games | Transportation | Travels |
| S.No. | Divisions | No. of Notebooks |
|---|---|---|
| 1 | Machine Learning (ML) | 29 |
| 2 | Deep Learning (DL) | 9 |
| 3 | Exploratory Data Analysis (EDA) | 24 |
| 4 | Time Series Analysis (TSA) | 12 |
| 5 | Natural Language Processing (NLP) | 14 |
| 6 | Image Processing Computer Vision (IPCV) | 10 |
| 7 | General Adverserial Network (GAN) | 3 |
| T | Total Works | 101 |