History of Java Language

                                   The Unmatched programming language that you will see on any software platform in the world 'java'. On 23 MAY 1995, JOHN GAGE, the director of the Science Office of the SUN MICROSYS- TEMS4 along with MARC ANDREESEN, co-founder and executive vice president at NETSCAPE announced to an audience of SunWorldTM that Java technology wasn’t a myth and that it was a realityandthatitwasgoingtobeincorporatedinto NETSCAPE NAVIGATOR. At...

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The heuristic method

                      In optimization problems, heuristic algorithms can be used to find a solution close to The Best Possible the optimal solution in cases where finding the optimal solution is impractical. These algorithms work by getting closer and closer to the optimal solution as they progress. In principle, if run for an infinite amount of time, they will find that optimal solution. Their merit is that they can find a solution very close to the optimal solution in a...

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Method 5:Hill Climbing Technique

                  Hill climbing is a technique for certain classes of optimization problems.This Methode is used by newton to find roots. The idea is to start with a sub-optimal solution to a problem (i.e., start at the base of a hill) and then repeatedly improve the solution (walk up the hill) until some condition is maximized (the top of the hill is reached). Hill-Climbing Methodology 1. Construct a sub-optimal solution that meets the constraints of the problem 2. Take the solution and make an improvement...

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Method 4: Greedy Algorithm

                         In the backtracking algorithms we looked at, we saw algorithms that found decision points and recursed over all options from that decision point. A greedy algorithm can be thought of as a backtracking algorithm where at each decision point "the best" option is already known and thus can be picked without having to recurse over any of the alternative options.                          The name...

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Memoization Methodology for backtracking

Memoization Methodology for backtracking 1. Start with a backtracking algorithm 2. Look up the problem in a table; if there's a valid entry for it, return that value 3. Otherwise, compute the problem recursively, and then store the result in the table before returning the value                                                    Consider the solution presented in the backtracking chapter for the Longest Common Subsequence...

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Method 3:Dynamic Programming

                   Dynamic Programming is another Method to develope new algorithm.  Dynamic programming can be thought of as an optimization technique for particular classes of backtracking algorithms where sub problems are repeatedly solved. Note that the term dynamic in dynamic programming should not be confused with dynamic programming languages, like Scheme or Lisp. Nor should the term programming be confused with the act of writing computer programs. In the context of algorithms, dynamic...

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Methode 2: Backtracking

Backtracking is a general algorithmic technique that considers searching every possible combination in order to solve an optimization problem. Backtracking is also known as depth-first search or branch and bound. By inserting more knowledge of the problem, the search tree can be pruned to avoid considering cases that don't look promising. While backtracking is useful for hard problems to which we do not know more efficient solutions, it is a poor solution for the everyday problems that other techniques are much better at solving.However, dynamic...

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Method 1: Inventing an algorithm.

The first major algorithmic technique is divide and conquer. This is the technique that britishers used to enter india. Part of the trick of making a good divide and conquer algorithm is determining how a given problem could be separated into two or more similar, but smaller, subproblems. More generally, when we are creating a divide and conquer algorithm we will take the following steps: Divide and Conquer Methodology 1. Given a problem, identify a small number of significantly smaller subproblems of the same type 2. Solve each subproblem recursively...

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Is Really Efficiency Required For Every Programme ?

When Efficiency is Important?                                     The Major Question in front of quite satisfactory Programmer.......  Not every problem requires the most efficient solution available. For our purposes, the term efficient is associated with the time or space needed to perform the task. When either time or space is abundant and cheap, it may not be worth it to pay a programmer to spend a day or so working to make a program faster. However,...

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Understanding an Algorithm

Understanding an Algorithm The Best Video that Decribes the Concept Algorithm Very good By  David J. Malan In TED-Ed Event.  source: youtube.com  publisher: TED-Ed ...

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Feedback About D3 Labs Workshop @IIT KGP by Prameel Arjun ,CEO of D3 labs.....

The Seminar Is good and really Benifited to me as I used blogs but i dont know how to use adsense and make most of my blogging. Based Upon the 1st day Workshop I will rate them as 4.5 out of 5.0. Also the Hacking Part is nicely introduced with some trick...

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Algorithms

The Good Algorithm Ensures Certain Things which enable it to be concise. The Crucial Things to be Kept in Mind While thinking an Algorithm are as follows :    the divide and conquer technique                                                                                                  ...

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About me

 My Details      Name- Amit Sanjay Patil                                                                                                                           e-mail address- apapapap44@gmail.com      ...

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