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Name: Veera Marni
Type: User
Location: Virginia
Name: Veera Marni
Type: User
Location: Virginia
algorithm preparation for interviews
Informatics class repo
Curated applications for Kubernetes
All class material
One of the most important task in computer vision is recognize handwritten digits. To perform this task we have many different algorithms some which are accurate to 100 %. Even tough these algorithms are simple enough to imple- ment their training times tend to grow quickly with high volumes of data. In today’s world where the data flows with a high velocity we need efficient algorithms that we can rely on in terms of time and space complexities. The goal of machine learning is to develop algorithms that generalize well to unseen data. However, many machine learning algorithms lack the capability to adapt to immediate changes as these algorithms take large times to converge to produce an optimum solution to a given problem. This paper compares the complexity analysis of a K-means and Neural Network algorithms that proved to work well with Digit recognition task and how the algorithms can be modified to result in an improvement both in terms of time and space complexity.
This repo includes all my works at IUB, but this may not be clear as it contains only the codes. For more details: Please take a look at my google drive https://drive.google.com/open?id=0B-jIy2XPN-32VU9oSmgtbHFUSDg
All data used in this project is from Kaggle walmart competition
Databases: Concepts, commands, codes, interview questions and more...
Includes various challenges from different sources I came across
contains various types of plots
Definition of Docker Image with composer included.
Git Source Code Mirror - This is a publish-only repository and all pull requests are ignored. Please follow Documentation/SubmittingPatches procedure for any of your improvements.
Must-read papers on graph neural networks (GNN)
ConfiguredGraphFactory of JanusGraph is very power full way to use a graph databases. I didn't find any readily available resources, so I trying put together something.
Example code from Learning Spark book
contains homeworks and others algo's developed
Code samples for my book "Neural Networks and Deep Learning"
How to export Org mode files into awesome HTML in 2 minutes
other minor works
Example project implementing best practices for PySpark ETL jobs and applications.
Org mode syntax reference card
sentiment Analysis for US_Election 2016
Deep Dive into Apache Spark 深入研读Spark源码
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.