se77enn Goto Github PK

1on1-questions

Mega list of 1 on 1 meeting questions compiled from a variety to sources

2048

A small clone of 1024 (https://play.google.com/store/apps/details?id=com.veewo.a1024)

6.824-lecture-notes

6.824 Distributed Systems: Lecture notes (edited a little and formatted with Markdown)

ai-programmer

Using artificial intelligence and genetic algorithms to automatically write a program, in the BrainF programming language. Read the tutorial at http://www.primaryobjects.com/cms/article149

algo

101+ coding interview problems in Go

algorithm-exercise

Data Structure and Algorithm notes. 数据结构与算法/leetcode/lintcode题解/

algorithms

Minimal examples of data structures and algorithms in Python

algorithms-and-coding-interviews

Open source content from a book in progress, Hands-on Algorithmic Problem Solving

algorithms.js

Atwood's Law applied to CS101 - Classic algorithms and data structures implemented in JavaScript

awesome-courses

:books: List of awesome university courses for learning Computer Science!

awesome-scalability

Scalable, Available, Stable, Performant, and Intelligent System Design Patterns

bitcoinbook

Mastering Bitcoin 2nd Edition - Programming the Open Blockchain

book

books

building-microservices-youtube

Code repository for my Building Microservices YouTube series https://www.youtube.com/playlist?list=PLmD8u-IFdreyh6EUfevBcbiuCKzFk0EW_

clrs

:notebook:Solutions to Introduction to Algorithms

clrs-1

Some exercises and problems in Introduction to Algorithms 3rd edition.

code

ActiveState Code Recipes

coding-interview-university

A complete computer science study plan to become a software engineer.

computer-science-resources

A list of resources in different fields of Computer Science (multiple languages)

course-nlp

A Code-First Introduction to NLP course

cpsc310-notes

Markdown notes for UBC CPSC 310: Introduction to Software Engineering.

csapp-3e

Solutions of Computer Systems: A Programmer's Perspective ,Third Edition

data-analysis

Data Science Using Python

data-science-interviews

Data science interview questions and answers

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

data-structure

data structure for competitive programming

deep-trading

Algorithmic trading with deep learning experiments

designing-data-intensive-applications-notes

Reading notes on the excellent "Designing Data-Intensive Applications"

dynamic-programming

Classical dynamic programming problems solution and algorithms