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Hi 👋, I'm Shivam Sharma

A Computer Science Graduate Who loves to Explore new Things.

shivamsharma009

shivamsharma009

Connect with me:

https://www.linkedin.com/in/shivam-sharma-9b708a174/ https://www.youtube.com/channel/UCNRHxbJqHMzlPlvgc8JYp9Q

Languages and Tools:

babel c docker flask git html5 java javascript kafka mongodb mysql nodejs rabbitMQ sass spring tensorflow

shivamsharma009

 shivamsharma009

shivamsharma009

Shivam Sharma's Projects

advanced-data-structure-and-algorithm icon advanced-data-structure-and-algorithm

Data Structures are used to store and manage data in an efficient and organised way for faster and easy access and modification of Data. Some of the basic data structures are Arrays, LinkedList, Stacks, Queues etc. This page will contain some of the complex and advanced Data Structures like Disjoint Sets, Self-Balancing Trees, Segment Trees, Tries etc.

algorithms icon algorithms

The word Algorithm means “a process or set of rules to be followed in calculations or other problem-solving operations”. Therefore Algorithm refers to a set of rules/instructions that step-by-step define how a work is to be executed upon in order to get the expected results.

data-structures icon data-structures

A data structure is a particular way of organizing data in a computer so that it can be used effectively.

dom icon dom

# document Object model

interview icon interview

# It Contains all of Famous Interview Questions

java-project-k-most-frequent-words-in-a-file icon java-project-k-most-frequent-words-in-a-file

Given a book of words. Assume you have enough main memory to accommodate all words. design a data structure to find top K maximum occurring words. The data structure should be dynamic so that new words can be added. A simple solution is to use Hashing. Hash all words one by one in a hash table. If a word is already present, then increment its count. Finally, traverse through the hash table and return the k words with maximum counts. We can use Trie and Min Heap to get the k most frequent words efficiently. The idea is to use Trie for searching existing words adding new words efficiently. Trie also stores count of occurrences of words. A Min Heap of size k is used to keep track of k most frequent words at any point of time Trie and Min Heap are linked with each other by storing an additional field in Trie ‘indexMinHeap’ and a pointer ‘trNode’ in Min Heap. The value of ‘indexMinHeap’ is maintained as -1 for the words which are currently not in Min Heap (or currently not among the top k frequent words). For the words which are present in Min Heap, ‘indexMinHeap’ contains, index of the word in Min Heap. The pointer ‘trNode’ in Min Heap points to the leaf node corresponding to the word in Trie.

low-level-design icon low-level-design

Low Level Designs of common data structures. These designs keep concurrency control, latency and throughput in mind. We use design patterns where applicable to make the code readable, extensible and testable.

machine-learning-algorithms icon machine-learning-algorithms

Machine Learning is the field of study that gives computers the capability to learn without being explicitly programmed. ML is one of the most exciting technologies that one would have ever come across. As it is evident from the name, it gives the computer that which makes it more similar to humans: The ability to learn. Machine learning is actively being used today, perhaps in many more places than one would expect.

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