Data Modeling Design

Read e-book online Big Practical Guide to Computer Simulations PDF

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  • Programming in C, fundamentals of C++, Python, make, shell scripts
  • Software engineering, computational provenance, model management
  • Debugging: gdb, reminiscence checking, profiling
  • Standard algorithms: generation, recursion, divide-and-conquer, dynamic programing, backtracking
  • Advanced info constructions: lists, bushes, tons, graphs
  • Libraries: normal C library, STL, GSL, self-written libraries
  • Randomness: chance, discrete and non-stop random variables, pseudo random numbers, inversion approach, rejection method
  • Data research: estimators, self assurance periods, histograms, resampling, plotting, Chi-squared try out, Kolmogorov-Smirnov try, ROC research, valuable part research, facts clustering, greatest chance, fitting
  • Presentation and publishing: gnuplot, xfig, Povray, LATEX