<ul><li>Dynamic programming is a method of solving problems with overlapping sub-problems and optimal substructures that can be optimised with the help of storing previously calculated solutions.</li><li>There are two approaches: top-down approach (memoization) and bottom-up approach (tabular method).</li><li>Dynamic programming can significantly reduce time complexity.</li><li>Memoization approach is a top-down approach where previously calculated solutions are stored in an array to eliminate redundancy.</li><li>The array is initialised with -1 and the values are filled for future use as required.</li><li>Tabular method is a bottom-up approach for dynamic programming where the solutions are iteratively calculated and stored in an array.</li><li>The array is filled from lower index to higher index in this case.</li><li>Memoization and tabular method have been explained using examples of generating Fibonacci numbers.</li><li>C++ programs for finding Fibonacci numbers using memoization and tabular method have been provided.</li><li>Dynamic programming is a powerful technique for optimisation of overlapping sub-problems.</li></ul>

Introduction to Dynamic Programming with example

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