This repo contains a series of guided jupyter notebooks focusing on essential ML concepts.
- Linear Regression
- Data Preprocessing
- Data Types and Attributes
- Binary Classification
- Clustering
- K-Nearest Neighbors (KNN)
- Naive Bayes
- Comprehensive EDA performed on "Data Science Jobs and Salary" dataset
- Comprehensive
- Practical Examples
- Easy to Understand
- Python
- Jupyter Notebook
- Learning: Use the notebooks to deepen your understanding of various ML concepts.
- Teaching: Share these notebooks with students to facilitate learning in classrooms or workshops.