All the essential resources and template code needed to understand and practice data structures and algorithms in python with few small projects to demonstrate their practical application.

Related tags

Deep Learningpythonalgorithmresourcespython3data-structurescomplexityoopsminiprojectsalgorithms-and-data-structures
Overview

Data Structures and Algorithms Python

INDEX

1. Resources -

  1. Books
    • Data Structures - Reema Thareja
    • competitiveCoding
  2. Big-O Cheat Sheet
  3. DAA Syllabus
  4. Interview Cheat sheet
  5. Master Plan
  6. Master the Interview

2. Big-O -

  1. O(1)
  2. O(m+n)
  3. O(n)
  4. O(n^2)

3. Data Structures -

  1. Arrays
  2. Graphs
  3. Hashtables (dictionary)
  4. Linked Lists
  5. Stack
  6. Queues
  7. Trees

4. Algorithms -

  1. Dynamic Programming
  2. Recursion
  3. Sorting
    • Bubble Sort
    • Heap Sort
    • Insertion Sort
    • Quick Sort
    • Selection Sort
  4. Traversals
    • BFS
    • DFS
    • Bisection Search

5. File Handling and OOPS

  1. File + Classes Demo

6. Projects

  1. Job Scheduler
  2. Email Project
  3. Hash Project
  4. Recursion Miniprojects
  5. Runtime Analyser
Owner
Shushrut Kumar
20 | Computer Science Engineering student at SRMIST Chennai
Shushrut Kumar
GitHub Repository
[ICCV 2021 Oral] Deep Evidential Action Recognition

DEAR (Deep Evidential Action Recognition) Project | Paper & Supp Wentao Bao, Qi Yu, Yu Kong International Conference on Computer Vision (ICCV Oral), 2

Wentao Bao 80 Jan 03, 2023
Mouse Brain in the Model Zoo

Deep Neural Mouse Brain Modeling This is the repository for the ongoing deep neural mouse modeling project, an attempt to characterize the representat

Colin Conwell 15 Aug 22, 2022
A Sign Language detection project using Mediapipe landmark detection and Tensorflow LSTM's

sign-language-detection A Sign Language detection project using Mediapipe landmark detection and Tensorflow LSTM. The project is built for a vocabular

Hashim 4 Feb 06, 2022
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language mod

20.5k Jan 08, 2023
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

Tensor2Tensor Tensor2Tensor, or T2T for short, is a library of deep learning models and datasets designed to make deep learning more accessible and ac

12.9k Jan 09, 2023
Human4D Dataset tools for processing and visualization

HUMAN4D: A Human-Centric Multimodal Dataset for Motions & Immersive Media HUMAN4D constitutes a large and multimodal 4D dataset that contains a variet

tofis 15 Nov 09, 2022
Pretraining Representations For Data-Efficient Reinforcement Learning

Pretraining Representations For Data-Efficient Reinforcement Learning Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Ch

Mila 40 Dec 11, 2022
Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images

Keras-ICNet [paper] Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images. Training in progress! Requisites Python 3.6.3 K

Aitor Ruano 87 Dec 16, 2022
Bachelor's Thesis in Computer Science: Privacy-Preserving Federated Learning Applied to Decentralized Data

federated is the source code for the Bachelor's Thesis Privacy-Preserving Federated Learning Applied to Decentralized Data (Spring 2021, NTNU) Federat

Dilawar Mahmood 25 Nov 30, 2022
Crowd-sourced Annotation of Human Motion.

Motion Annotation Tool Live: https://motion-annotation.humanoids.kit.edu Paper: The KIT Motion-Language Dataset Installation Start by installing all P

Matthias Plappert 4 May 25, 2020
Official implementation of the paper "AAVAE: Augmentation-AugmentedVariational Autoencoders"

AAVAE Official implementation of the paper "AAVAE: Augmentation-AugmentedVariational Autoencoders" Abstract Recent methods for self-supervised learnin

Grid AI Labs 48 Dec 12, 2022
Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA)

Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA). Master's thesis documents. Bibliography, experiments and reports.

Erick Cobos 73 Dec 04, 2022
ANEA: Distant Supervision for Low-Resource Named Entity Recognition

ANEA: Distant Supervision for Low-Resource Named Entity Recognition ANEA is a tool to automatically annotate named entities in unlabeled text based on

Saarland University Spoken Language Systems Group 15 Mar 30, 2022
A PyTorch toolkit for 2D Human Pose Estimation.

PyTorch-Pose PyTorch-Pose is a PyTorch implementation of the general pipeline for 2D single human pose estimation. The aim is to provide the interface

Wei Yang 1.1k Dec 30, 2022
A quantum game modeling of pandemic (QHack 2022)

Contributors: @JongheumJung, @YoonjaeChung, @GyunghunKim Abstract In the regime of a global pandemic, leaders around the world need to consider variou

Yoonjae Chung 8 Apr 03, 2022
This git repo contains the implementation of my ML project on Heart Disease Prediction

Introduction This git repo contains the implementation of my ML project on Heart Disease Prediction. This is a real-world machine learning model/proje

Aryan Dutta 1 Feb 02, 2022
A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available.

Use this instead: https://github.com/facebookresearch/maskrcnn-benchmark A Pytorch Implementation of Detectron Example output of e2e_mask_rcnn-R-101-F

Roy 2.8k Dec 29, 2022
Pre-Training Graph Neural Networks for Cold-Start Users and Items Representation.

Pretrain-Recsys This is our Tensorflow implementation for our WSDM 2021 paper: Bowen Hao, Jing Zhang, Hongzhi Yin, Cuiping Li, Hong Chen. Pre-Training

30 Nov 14, 2022
From Fidelity to Perceptual Quality: A Semi-Supervised Approach for Low-Light Image Enhancement (CVPR'2020)

Under-exposure introduces a series of visual degradation, i.e. decreased visibility, intensive noise, and biased color, etc. To address these problems, we propose a novel semi-supervised learning app

Yang Wenhan 117 Jan 03, 2023
Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary Differential Equations

ODE GAN (Prototype) in PyTorch Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary

Somshubra Majumdar 15 Feb 10, 2022