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- Undergraduate Level:
- "Introduction to Algorithms" by
Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford
Stein
- "Computer Networks" by Andrew
S. Tanenbaum and David J. Wetherall
- "Operating System Concepts" by
Abraham Silberschatz, Peter B. Galvin, and Greg Gagne
- "Database System Concepts" by
Abraham Silberschatz, Henry F. Korth, and S. Sudarshan
- "Artificial Intelligence: A Modern
Approach" by Stuart Russell and Peter Norvig
- Post-graduate Level:
- "Pattern Recognition and Machine
Learning" by Christopher M. Bishop
- "Computer Architecture: A
Quantitative Approach" by John L. Hennessy and David A. Patterson
- "Introduction to the Theory of
Computation" by Michael Sipser
- "Data Mining: Concepts and
Techniques" by Jiawei Han, Micheline Kamber, and Jian Pei
- "Software Engineering: A
Practitioner`s Approach" by Roger S. Pressman
- MPhil/PhD Level:
- "Introduction to Information
Retrieval" by Christopher D. Manning, Prabhakar Raghavan, and
Hinrich Schütze
- "Computer Vision: Algorithms and
Applications" by Richard Szeliski
- "The Elements of Statistical
Learning: Data Mining, Inference, and Prediction" by Trevor Hastie,
Robert Tibshirani, and Jerome Friedman
- "Deep Learning" by Ian
Goodfellow, Yoshua Bengio, and Aaron Courville
- "Distributed Systems: Principles and
Paradigms" by Andrew S. Tanenbaum and Maarten Van Steen
These books cover a
wide range of topics in Computer Science, from algorithms and data structures
to artificial intelligence and distributed systems, and are widely used as
reference materials in academic coursework.
