Popular computer science books for post-graduate courses

In terms of post-graduate coursework offered in IITs, I have compiled a list of such books that are usually referred.

Advanced Algorithms

  1. Foundations of Algorithms, Jones and Bartlett. [Site]
  2. Algorithm Design by Jon Kleinberg and Eva Tardos [PDF]

Social Computing :

  1. Networks, Crowds, and Markets – Easley and Kleinberg [PDF]
  2. Mining of Massive Datasets – Jure Leskovec, Anand Rajaraman, Jeff Ullman [PDF] – I personally bought this book and found it to be very useful. It introduces each topic and also explores the modification of the algorithm on a large scale, i.e., when running on a large number of data points.

Machine Learning

  1. Pattern Classification, Duda Hart – A fair warning that it contains a fair bit of maths and is recommended for those new to the field. [PDF]
  2. Tom Mitchell. Machine Learning (McGraw Hill) – I will recommend this book if you are just starting. The concepts are explained quite lucidly. [PDF]
  3. Pattern Recognition – an Algorithmic Approach – I personally found this book to be quite easy to grasp.
  4. Machine Learning – a probabilistic perspective by Kevin P. Murphy – This book gives a good mathematical treatment in explaining Machine Learning concepts. [PDF]

Deep Learning

  1. Deep Learning by Ian Goodfellow and Yoshua Bengio and Aaron Courville[PDF]

Natural Language Processing

  1. Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition by Jurafsky and Martin [PDF]

Information Retrieval

  1. Introduction to Information Retrieval by Manning, Raghavan and Schutze[PDF]
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