



  Introduction to the Design and Analysis of Algorithms (3rd Edition)
Based on a new classification of algorithm design techniques and a clear delineation of analysis methods, Introduction to the Design and Analysis of Algorithms presents the subject in a coherent and innovative manner. Written in a studentfriendly style, the book emphasizes the understanding of ideas over excessively formal...   


    Data Structures and Algorithms Using Python and C++
THIS BOOK is intended for use in a traditional collegelevel data structures course (commonly known as CS2). This book assumes that students have learned the basic syntax of Python and been exposed to the use of existing classes. Most traditional CS1 courses that use Python will have covered all the necessary topics, and some may have covered a... 

Data Mining: Concepts, Models, Methods, and Algorithms, Second Edition
Now updated—the systematic introductory guide to modern analysis of large data sets
As data sets continue to grow in size and complexity, there has been an inevitable move towards indirect, automatic, and intelligent data analysis in which the analyst works via more complex and sophisticated software tools. This book...   Computational Geometry: Algorithms and Applications, Second Edition
This wellaccepted introduction to computational geometry is a textbook for highlevel undergraduate and lowlevel graduate courses. The focus is on algorithms and hence the book is well suited for students in computer science and engineering. Motivation is provided from the application areas: all solutions and techniques from computational...   Python Data Science Handbook: Essential Tools for Working with Data
For many researchers, Python is a firstclass tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib,... 


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