Top Algorithms for Performance and Efficiency

Originally aired:

About the Session

We are all proud of being the best coders, but have we analyzed our code for optimization? What tools can help us guide toward creating algorithms with better time and space complexity?

How you approach a problem is critical. How do you solve the problem? How do you optimize the problem?

This talk will not only prepare you for the interviews but will also give confidence on how to crack the coding challenges.

In this talk, we will be exploring analytical skills and coding skills of the top algorithms and common problems from the real-world, including

  •     Single Source Shortest Paths
  •     Traveling Salesman problems
  •     Pattern Search Algorithms
  •     Greedy Algorithms
  •     KnapSack problem
  •     Priority queue

Problem-solving skills are valuable and help develop optimal algorithms. We will look at problem-solving flow charts to make the right decisions for a given problem.

Topics we will cover are:

  •     Arrays and Strings - Palindrome permutations
  •     Linked Lists - Runner technique, Recursions
  •     Stacks and queues
  •     Trees and Graphs - Binary Tree, Binary Search Tree, Tries
  •     Sorting and Searching
  •     Single-Source Shortest Paths: Bellman-Ford, BFS, DFS, Dijkstra, Dynamic Programming

This talk is ideal for the following roles:

  •     Architects
  •     Technical Leads
  •     Programers
  •     Integration Architects
  •     Solution Architects

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