trishala1095 Goto Github PK
Type: User
Bio: Data Scientist Intern at Teradata | Master's Student at NJIT | Data Enthusiast | Machine learning engineer | Data analyst
Location: San Diego
Type: User
Bio: Data Scientist Intern at Teradata | Master's Student at NJIT | Data Enthusiast | Machine learning engineer | Data analyst
Location: San Diego
Implementing Apriori algorithm from scratch in JAVA.
A step-by-step guide for creating a books recommendation system using Cosine similarity in python.
basic implementation of CNN in python
he project implements time series forecasting of Financial Stock Prediction of SPDR Gold Shares(GLD) from Yahoo Finance using RNN LSTM in Keras.The project is written in Python 3. Packages like tensorflow, keras and scikit-learn were used for implementation. Data visualization and processing were represented through the matplotlib packages.The aim of the project is to analyze the historical data of GLD stocks from year 2004 to year 2020 and predict the values for the next day. Stock predictions give efficient hypotheses to attain great profits.
In this project, an Oozie based workflow is developed to analyze the on-time performance of airline data from the period of October 1987 to April 2008. The flight data analyzed can be downloaded from the link below: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/HG7NV7 One java program consisting of three MapReduce programs are used to analyze the flight dataset. Each MapReduce program solves one of the following problems using Oozie workflow : A) B) C) The 3 airlines with the highest and lowest probability, respectively, for being on schedule. The 3 airports with the longest and shortest average taxi time per flight (both in and out), respectively. The most common reason for flight cancellations.
A simple graphical representation of famous fantasy TV series, Game of Thrones using Python NetworkX.
A test to get coloring working in NetworkX
Java implementation of poker card game.
Developed a Hadoop based MapReduce program to compute the relative frequencies of each word that occurs in all the documents in 100KWikiText.txt, and output the top 100 word pairs sorted in a decreasing order of relative frequency. Relative frequency of word B given word A is defined as follows: f(B|A) = count(A,B)/count(A) where count(A,B) is the number of times A and B co-occur in a document, and count(A) the number of times A occurs with anything else. Intuitively, given a document collection, the relative frequency captures the proportion of time the word B appears in the same document as A.
A simple explorative way to dig into data of Spotify songs using python and Spotipy python library.
A specialized R program to crawl, parse and extract useful information from online websites.
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.