Exploring the Best Books for GATE Data Science Preparation
Introduction:
Data Science is an ever-evolving field that demands a solid foundation in various aspects, including probability, linear algebra, calculus, programming, algorithms, databases, machine learning, and artificial intelligence. As aspiring GATE (Graduate Aptitude Test in Engineering) candidates, it’s crucial to have access to high-quality resources that cover these topics comprehensively. In this article, we will explore some of the best books for GATE Data Science preparation.
- “Introduction to Probability and Statistics for Engineers and Scientists” by Sheldon M. Ross
This book by Sheldon M. Ross provides a solid foundation in probability and statistics, essential for understanding various data science concepts. Download from here: Read here - “Introduction to Linear Algebra” by Gilbert Strang
Gilbert Strang’s “Introduction to Linear Algebra” is a widely acclaimed resource for gaining a deep understanding of linear algebra, a fundamental aspect of data science. Download from here: Read here - “Calculus” by Gilbert Strang
Another gem by Gilbert Strang, this book covers calculus, providing a strong mathematical foundation necessary for data science applications. Download from here: Read here - “Deep Learning” by Ian Goodfellow, Yoshua Bengio, Aaron Courville
This book is a comprehensive guide to deep learning, a crucial aspect of modern data science. Authored by experts, it covers the theoretical and practical aspects of deep learning. Download from here: Read here - “Python Programming: The Ultimate Beginner’s Guide to Learn Python Step by Step” by Ryan Turner Ryan Turner’s book is an excellent resource for beginners, providing a step-by-step guide to learning Python, a language widely used in data science.
- “Introduction to Algorithms” by Thomas H. Cormen et al.
For a thorough understanding of algorithms, this book is a classic reference, offering insights into various algorithmic techniques and their applications. Download from here: Read here - “Database System Concepts” by Avi Silberschatz, Henry F. Korth, S. Sudarshan
Databases are a crucial component of data science, and this book provides a comprehensive understanding of database system concepts. Download from here: Read here - “Hands-On Machine Learning with Scikit-Learn and TensorFlow” by Aurélien Géron
This hands-on guide focuses on practical aspects of machine learning using popular Python libraries like Scikit-Learn and TensorFlow. Download from here: Read here - “Artificial Intelligence: A Modern Approach” by Stuart Jonathan Russell, Peter Norvig, Ernest Davis
This book is a comprehensive guide to artificial intelligence, covering both traditional and modern approaches to AI. Download from here: Read here
Conclusion:
For GATE Data Science aspirants, these books serve as valuable resources to build a strong foundation and excel in various aspects of data science. Whether you’re diving into probability, linear algebra, calculus, programming, algorithms, databases, or machine learning, these books cover it all, providing a holistic approach to GATE preparation in the field of Data Science. Happy learning!