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acmfinalssolutions

SnapDragon's solutions for the ACM ICPC World Finals problems.

algo

algo-lib

Concise, performant data structures and algorithms in C++.

algorithms

Implementations of algorithms used for competitive programming, with a focus placed on readability, usability, conciseness, and performance (when important)

algorithms-1

A collection of algorithms and data structures

awesome-competitive-programming

:gem: A curated list of awesome Competitive Programming, Algorithm and Data Structure resources

awesome-java

A curated list of awesome frameworks, libraries and software for the Java programming language.

codebook

Reference material for ACM-ICPC

codes

This repository contains all my codes for the competitive programming from Codeforces, Hackerrank, Codechef and others

competitive-coding

Some useful templates and reading material for competitive coding.

competitive-programming

Solutions to problems from various online judges / contest sites.

complete-guide-to-elasticsearch

Contains all of the queries used within the Complete Guide to Elasticsearch course.

cpp-stl-algorithms

This repository houses VERY simple example code for each STL algorithm and explains what each does.

cracking-the-data-science-interview

A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep

cses_solution

Range_Queries

data-processing-with-logstash

Contains the configuration files used within the Data Processing with Logstash course.

deep-learning

Assignmends done for Udacity's Deep Learning MOOC with Vincent Vanhoucke

dom-array-methods

Wealth calculator app with random user api built with javascript es6 array methods

ds-cheatsheets

List of Data Science Cheatsheets to rule the world

effective-java-summary

Summary of the book Effective Java 2nd Edition by Joshua Bloch

elasticsearch-rest-client-samples

Elasticsearch REST client samples using Testcontainers

gcc

graph

cses solution

icpc_notebook

Team notebook of Trie_NP_Hard

kmq

Kafka-based message queue

lab01-nosql

lectures

Oxford Deep NLP 2017 course

machine-coding-feedback-learn

microservices

ml-from-scratch

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.