You can look into the following books in this context:

1) Linear Models in Statistics by Rencher and Schaalje

2) Applied Regression Analysis by Draper and Smith

I am a bit puzzled, what kind of software do you use? If you want to use exercises, it would be helpful to know which software (and why not R in particular...).

Kutner, Nachtsheim, Neter, Li: Applied Linear Statistical Models

Gelman, Hill: Data Analysis Using Regression and Multilevel/Hierarchical Models

Harrell: Regression Modelling Strategies

Dobson, Barnett: Generalized Linear Models

Fox: Applied Regression Analysis & Generalized Linear Models

Hello Javed Iqbal This is also a good book in my opinion, if you are looking to understand concepts and theories focusing on mathematical sciences and statistics.

https://www.utstat.toronto.edu/~brunner/books/LinearModelsInStatistics.pdf

The book includes exercises at the end of each chapter, and at the end of the book, there are solutions to the exercises and answers to the questions of each chapter. It is useful for you who want to be teachers of students.

“The Elements of Statistical Learning” by Trevor Hastie, Robert Tibshirani, and Jerome Friedman shines as a beacon of knowledge, offering a comprehensive and invaluable resource for understanding the principles that underpin machine learning and statistical modeling. You should use your prior experience in statistics and probability as a starting point for your journey into statistical modeling, if you have a background in these fields. For example, you should learn the basics of regression analysis and the relevant tools, and become comfortable interpreting analysis results.