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apriori-algorithm-implementation

Implementing Apriori algorithm from scratch in JAVA.

books-recommendation-system

A step-by-step guide for creating a books recommendation system using Cosine similarity in python.

convolution-neural-network

basic implementation of CNN in python

financial-stock-prediction

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.

flight-data-analysis

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.

got-networkx-analysis

A simple graphical representation of famous fantasy TV series, Game of Thrones using Python NetworkX.

kkbox-s-churn-prediction

networkx-twitter-analysis

A test to get coloring working in NetworkX

poker-card-game

Java implementation of poker card game.

relative-frequencies-of-words

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.

social-media-news-recommendation

spotify-data-analysis

A simple explorative way to dig into data of Spotify songs using python and Spotipy python library.

university-of-liverpool--ion-switching

usa-crime-analysis-using-k-means-clustering

web-crawler

A specialized R program to crawl, parse and extract useful information from online websites.