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advanced-java

😮 互联网 Java 工程师进阶知识完全扫盲：涵盖高并发、分布式、高可用、微服务、海量数据处理等领域知识，后端同学必看，前端同学也可学习

awesome-for-beginners

A list of awesome beginners-friendly projects.

awesome-interview-questions

:octocat: A curated awesome list of lists of interview questions. Feel free to contribute! :mortar_board:

booki

Booki Project 📖 Fully working Angular 7 - Java EE Spring Boot Application ❤️

books

cheatsheets

Various cheetsheats for LaunchCode Education content

course-collaboration-travel-plans

ctci-6th-edition-python

Cracking the Coding Interview 6th Ed. Python Solutions

d3

Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada:

datacamp

DataCamp data-science courses

eeg-classification

Classification of eeg signals using knn and svm based upon significant features

epilipsy-seizure-info-form

get information from epilipsy pateints about their frequency,pattern,time,after injuries, age,gender, and side notes

every-programmer-should-know

A collection of (mostly) technical things every software developer should know

google-cloud-java

Google Cloud Client Library for Java

hacker-rank-matching-book-names-and-descriptions-solution

Our bot has crawled several product pages from the popular Indian e-commerce website, Flipkart.com. All of these pages are specifically about the most popular books being sold on Flipkart (at the time of the crawl). Each page contained information for exactly one book. We noted down exactly two fields from each of these pages: 1. The name of the book. 2. Description fragment: The first few sentences of the description of the book, as displayed on the page. In some cases, this string or text field might be terminated prematurely (i.e., not exactly at a word or a sentence boundary). Each of these text blocks is split into two parts of roughly equal length. Set A contains the names of all the books. Set B contains the description fragments for all the books. Both the Sets A and B are shuffled up, and the ordering of elements is lost. Your task is to identify, for each name (a) in Set A, which is the correct corresponding text fragment (b) in Set B, such that, b was the descriptive fragment for the book named a. Hints: Getting started - Think about using TF-IDF Scores (or a modification of it) For those getting started with this fascinating domain of text classification, here's a wonderful Youtube video of Professor Christopher Manning from Stanford, explaining the TF-IDF , which you could consider using as a starting point. Input Format An Integer N on the first line. This is followed by 2N+1 lines. Text fragments (numbered 1 to N) from Set A, each on a new line (so a total of N lines). A separator with five asterisk marks "*" which indicates the end of Set A and the start of Set B. Text fragments (numbered 1 to N) from Set B, each on a new line (so a total of N lines). Output Format N lines, each containing one integer. The i-th line should contain an integer j such that the j-th element of Set A and the i-th element of Set B are a pair, i.e., both originally came from the same listing page on Flipkart. Constraints 1 <= N <= 1000 No text fragment will have more than 10000 characters. Sample Input 5 How to Be a Domestic Goddess : Baking and the Art of Comfort Cooking (Paperback) Embedded / Real-Time Systems 1st Edition (Paperback) The Merchant of Venice (Paperback) Lose a Kilo a Week (Paperback) Few Things Left Unsaid (Paperback) ***** Today the embedded systems are ubiquitous in occurrence, most significant in function and project an absolutely promising picture of developments in the near future. The Merchant Of Venice is one of Shakespeare's best known plays. How To Be A Domestic Goddess: Baking and the Art of Comfort Cooking is a bestselling cookbook by the famous chef Nigella Lawson who aims to introduce the art of baking through text with an emphasis. Lose A Kilo A Week is a detailed diet and weight loss plan, and also shows how to maintain the ideal weight after reaching it. Few Things Left Unsaid is a story of love, romance, and heartbreak. Sample Output 2 3 1 4 5 Explanation Explaining the Input The first line indicates that the test case contains the names and descriptions of five popular books listed on Flipkart. The next five lines are the names of the books (i.e, Set A). After that, we have a separator. That is followed by five lines, each containing description fragments from Set B. Explaining how we arrived at the Output The first description, is visibly most closely related to the second book (Embedded / Real-Time Systems 1st Edition (Paperback)). The second description, is clearly about the Merchant of Venice - which is the third book name in Set-A. The third description is about Baking - and so, it corresponds to the first of the book names, in Set-A. Similarly, the fourth and fifth descriptions match best with the fourth and fifth book names (i.e, it so happens that they are already in order). So, the expected output is 2, 3, 1, 4, 5 respectively. Scoring The weight for a test case will be proportional to the number of tests (book names) it contains. Two sample tests are available and visible on Compile & Test. A training driven approach or solution is not expected in this challenge, which is why no comprehensive training data has been provided. Score = M * (C)/N Where M is the Maximum Score for the test case. C = Number of correct answers in your output. N = Total number of book names in the test set (which were divided into Set A and Set B respectively). Note: Submissions will be disqualified if it is evident that the code has been written in such a way that the sample test case answers are hard-coded, or similar approaches, where the answer is not computed, but arrived at by trying to ensure the code matches the sample answers. Timelimits Timelimits can be seen here. Libraries Libraries available in our Machine Learning/Real Data challenges will be enabled for this contest and are listed here. Please note, that occasionally, a few functions or modules might not work in the constraints of our infrastructure. For instance, some modules try to run multiple threads (and fail). So please try importing the library and functions and cross checking if they work in our online editor in case you plan to develop a solution locally, and then upload to our site.

interview_solutions

200 efficient solutions to must-know interview problems

javaguide

【Java学习+面试指南】 一份涵盖大部分Java程序员所需要掌握的核心知识。

kaggle-eeg

Kaggle/Uni Melbourne seizure prediction

kaggle-seizure-prediction-challenge-2016

Code and documentation for the winning solution to the Melbourne University AES/MathWorks/NIH Seizure Prediction challenge on kaggle

learnangular

Repository for my Learn Angular Course

lectures

Oxford Deep NLP 2017 course

leetcode-problems

daily leetcode problems [start date:13 March 2021]

leetcode_practice

piggymetrics

Microservice Architecture with Spring Boot, Spring Cloud and Docker

pizza-calorie-calculator

this project uses tensorflow to retrain inception neural network to recognize differrent pizaa categories

pycon2017

the repository contains the workshop material I presented in pycon 2017 in Pakistan

spring-cloud-alibaba

Spring Cloud Alibaba provides a one-stop solution for application development for the distributed solutions of Alibaba middleware.

spring-in-action-5-samples

Home for example code from Spring in Action 5.

thingsboard

Open-source IoT Platform - Device management, data collection, processing and visualization.

zipkin

Zipkin is a distributed tracing system