Introduction to computation and programming using Python :
Guttag, John
Introduction to computation and programming using Python : with application to understanding data John Guttag - Second edition - Delhi : PHI Learning, 2017. - xvii, 447 pages ; 23 cm
Introduction to Python Some simple numerical programs Functions, scoping, and abstraction Structured types, mutability, and higher-order functions Testing and debugging Exceptions and assertions Classes and object-oriented programming A simplistic introduction to algorithmic complexity Some simple algorithms and data structures Plotting and more about classes Knapsack and graph optimization problems Dynamic programming Random walks and more about data visualization Stochastic programs, probability, and distributions Monte Carlo stimulation Sampling and confidence intervals Understanding experimental data Randomized trials and hypothesis checking Conditional probability and Bayesian statistics Lies, damned lies, and statistics A quick look at machine learning Clustering Classification methods
The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization.
9788120352926
Computer programming
Object-oriented programming (Computer science)
Python (Computer program language)
005.133 / GUT
Introduction to computation and programming using Python : with application to understanding data John Guttag - Second edition - Delhi : PHI Learning, 2017. - xvii, 447 pages ; 23 cm
Introduction to Python Some simple numerical programs Functions, scoping, and abstraction Structured types, mutability, and higher-order functions Testing and debugging Exceptions and assertions Classes and object-oriented programming A simplistic introduction to algorithmic complexity Some simple algorithms and data structures Plotting and more about classes Knapsack and graph optimization problems Dynamic programming Random walks and more about data visualization Stochastic programs, probability, and distributions Monte Carlo stimulation Sampling and confidence intervals Understanding experimental data Randomized trials and hypothesis checking Conditional probability and Bayesian statistics Lies, damned lies, and statistics A quick look at machine learning Clustering Classification methods
The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization.
9788120352926
Computer programming
Object-oriented programming (Computer science)
Python (Computer program language)
005.133 / GUT