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evospark

feature-engineering-in-pyspark

Application of PySpark on the big data of finance and accounting measures to built an optimized portfolio

feature_generator_in_spark

Utilize sci-kit learn library to assist in optimizing machine learning feature generation within Spark environment

gaft

A Genetic Algorithm Framework in Python (This repo is for learning purpose, NOT production)

genetic-cnn

CNN architecture exploration using Genetic Algorithm

gentun

Hyperparameter tuning for machine learning models using a distributed genetic algorithm

hadoop-particle-swarm-optimization

Map Reduce based Stochastic Particle Swarm Optimization

helpingsantashelpers

Code for the Kaggle 2014 Holiday Competition: Helping Santa's Helpers

hypernn

Academic project to optimize neural network hyper parameters.

jmetalsp

A framework for Big Data Optimization with multi-objective metaheuristics

kmpso

KMeans-PSO Clustering algorithem base on apache spark

learning-spark

Example code from Learning Spark book

mapreduce-based-deep-learning

2013 Fall Cloud Computing Project for Nerve Cloud group: MapReduce-Based Deep Learning

mapreduce-based-deep-learning-with-handwritten-digit-recognition-python-implementation-

Apply mapreduce idea into Deep-Learning for Handwritten-Digit-Recognition

medea_bmc_article

LaTeX sources for the J. Chem. Inf. article on Medea

median_solver

micmat

MICMat is a Python interface for Intel's Xeon Phi.

minority-type-imbalanced

models

Models and examples built with TensorFlow

movie-recommender-system-in-spark

Implementing a Recommender System in Spark to predict ratings of movies. Utility matrix is based on the Movie Lens dataset. Using the Products of Factors technique for the system and optimizing the loss function with ALS.

mr_psofcm

PSO and FCM algorithm Using MapReduce

mrpso

multi-kmeans-spark

BDA @ FII Iasi Project task - k-means implementations

optimize-cnns-using-spark

(OnGoing) Deep learning algorithm optimization with MapReduce framework of Apache Spark.

parallel-pso-spark

Parallel Particle Swarm Optimizer on the Spark Clustering Computing Platform.

parallel-text-processing-using-spark

Analysis of Latin documents provided by Classics department of University of Buffalo. Performed normalization and lemmatization on the latin texts. Scaled the number documents from 2 to 80 and compared the performance on scaling and optimized the algorithm for better performance. Tools: VMWare

patch-hfss

Optimization of Patch Antenna using QPSO

ppcloudcomputing

《云计算原理与实践》教材的配套资源

pso

qpso

psoalgorithms

This is my undergraduate thesis about high-performance discrete particle swarm optimization (PSO) algorithm and software development of application on JSSP problem.