This repo contains exercises for Distributed ML: Using Spark.
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Updated
Feb 26, 2021 - Jupyter Notebook
This repo contains exercises for Distributed ML: Using Spark.
This repo includes a TF estimator implemented in Amazon SageMaker, distributed over 2 nodes.
[arXiv] Decentralized Multi-Target Cross-Domain Recommendation for Multi-Organization Collaborations
Comparison of distributed machine learning techniques applied to openly available datasets
Distributed Neural Networks Training
[DCC 2020] DRASIC: Distributed Recurrent Autoencoder for Scalable Image Compression
A quick library for Distributed Machine Learning which includes a matrix-math utils library built around CUDA kernels.
Master-slave distributed system that works together to speed up the kNN classification.
Scalable NLP model fine-tuning and batch inference with Ray and Anyscale
distributed sgd implementation with tensorflow and mpi4py.
Distributed problem solving using Machine Learning : K-Medoids Clustering
Distributed Machine Learning with Apache Spark (CS120x)(Edx) Assignment Solutions
Robust P2P Personalized Learning
Distributed Machine Learning Studio
Simulation of distributed SVM
Java based Convolutional Neural Network package running on Apache Spark framework
The course studies fundamentals of distributed machine learning algorithms and the fundamentals of deep learning. We will cover the basics of machine learning and introduce techniques and systems that enable machine learning algorithms to be efficiently parallelized.
Machine Learning assignments, Machine Learning (IE500618) course, fall 2022.
This is a bibliography survey upon Distributed Machine Learning. The survey contains algorithmic selections and architectures that can facilitate distributed learning on ML models. There is also a part that presents MLlib, a ML library from Apache Spark for distributed ML implementations.
Implementation of asynchronous federated learning in flower.
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