Introduction¶
This book contains reading materials and notes for students enrolled in Coding Blocks’s Data Science Master Course. It is intended to be used as a supplementary material along with the course content. The book contains two sections that covers topics in Machine Learning and Deep Learning.
Attention
The topics covered and the contents provided in this book is in active development. If you find any mistakes or want to report missing topics or information. Refer to Contributing.
The book is organised as follows.
Machine Learning
- Numpy
- Matplotlib: Visualization with Python
- Pandas
- K - Nearest Neighbour
- Linear Regression
- Multi Variable Regression
- MLE - Linear Regression
- Generalised linear model-Linear Regression
- Gradient Descent
- Logistic Regression
- Logistic Regression MLE & Implementation
- Decision Tree Algorithm
- Ensemble Learning
- Naive Bayes Algorithm
- Multinomial Naive Bayes
- Imbalanced Dataset
- Principal Component Analysis
About
Important
Section II of the book is currently in development phase. We are actively looking for interns to work on the same. If you wish to be a part, mail to manu.pillai@codingblocks.com