Prashant Chaubey's starred repositories
TopReviewedWebsite
Hadoop project to read xml file using MapReduce, Pig, Hive, Sqoop, MySQL
SoftwareEngr-MapReduce
MapReduce Usage and Implementation for Software Engineering 2017 Final Project
crystalball
A Naive Bayes Text Classifier implemented in Apache Hadoop MapReduce.
Twitter-sentiment-analysis
Python coded sentiment analysis using machine learning and imported code to Hadoop MapReduce.
MapReduce-Project
A thorough analysis of an inspection result of over 448,000 restaurants in New York City. Used MapReduce
handson-ml
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
svm_mnist_digit_classification
MNIST digit classification with scikit-learn and Support Vector Machine (SVM) algorithm.
multiclassSVM
Experiments on creating an SVM that can perform multi-class classification
large-scale-ml
Implementation of standard Large Scale ML algorithms for Perceptrons, SVM and KNN Joins using MapReduce
MapReduce-Machine-Learning
Map-Reduce implementation of some machine learning algorithms
recsys-mapreduce-mrjob
Examples of Recommendations powered by MapReduce and mrjob
SVM-mapreduce
A map reduce approach to SVM classification. http://r-es.org/Concursos+V+Jornadas
Parallel_SVMs
The quantity of electronic data available for analysis has grown exponentially with the rapid development of the World Wide Web, the Internet of Things, and other digital technologies. As a result, data mining and machine learning algorithms face computational complexity issues when applied to real world datasets. Support Vector Machines (SVM) are powerful classifcation and regression tools but their computational requirements increase rapidly as the number of training examples increases. To address this problem, several parallel MapReduce based implementations of SVMs have been proposed. These implementation have in common that they decompose a large-scale multi-class problem to a number of relatively smaller subproblems by dividing the data into multiple partitions which can be processed in parallel; however, these approaches use different aggregation and combination strategies to form the final model.In this project, we implement three parallel SVM algorithms on the Hadoop implementation of MapReduce, using the LibSVM library for core SVM computations. We conduct a comprehensive investigation of the three algorithms in order to compare their generalization performance, accuracy, and training times.
MachineLearningOnYelpDataset
Predict the degree of likeness for new yelp businesses using Machine Learning
MapReduce-Based-Deep-Learning
2013 Fall Cloud Computing Project for Nerve Cloud group: MapReduce-Based Deep Learning