https://github.com/code-lucidal58/dsa-python

Data Structures and Algorithms using Python
https://github.com/code-lucidal58/dsa-python

data-structure-and-algorithm data-structures python python3

Last synced: 16 days ago
JSON representation

Data Structures and Algorithms using Python

• Host: GitHub
• URL: https://github.com/code-lucidal58/dsa-python
• Owner: code-lucidal58
• Created: 2019-02-20T18:44:28.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2020-05-17T13:40:12.000Z (almost 5 years ago)
• Last Synced: 2025-03-27T08:11:19.362Z (about 1 month ago)
• Topics: data-structure-and-algorithm, data-structures, python, python3
• Language: Jupyter Notebook
• Size: 31.3 KB
• Stars: 5
• Watchers: 1
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Python for Data Structures, Algorithms, and Interviews!

This repository consists of notes made while going through the course *Python for Data Structures, Algorithms, and Interviews!* 

in Udemy. All modules are separated as Jupiter Notebooks.

This course mainly has questions based on different data structures and very less questions based on pre-known algorithms.

Kindly refer to [my repo](https://github.com/code-lucidal58/named-algorithms) for list of named algorithms and their implementations.

All the best and keep coding!! :)

## Algorithms characteristics:

Algorithms have associated complexity:  

* space -> memory occupied  

* time -> time taken to complete task irrespective of input size  

* They have set of input and produces output

#Algorithms classification  

* series-> sequential fashion

* parallel -> break data set and work on each simultaneously

* exact -> provides exact value as output

* approximate -> output may or may not be exact e.g. face recognition

* deterministic -> steps know

* non-deterministic -> based on guesses

## Types of Algorithms

* searching -> search specific data in a larger data

* sorting -> sort a dataset

* computational -> take one data set and return another data set

* collection -> navigating through elements in a dataset

## Algorithms performance

Big-O notation: classifies performance as input size grows. O represents order of operation

  

    Notation

    Description

  

  

    O(1)

    Constant

  

  

    O(log n)

    Logarithmic

  

  

    O(n)


    Linear time

  

  

    O(nlogn)

    Log-linear

  

  

    O(n^2)

    Quadratic