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- Wekadeeplearning4j: a Deep Learning Package for Weka Based on Deeplearning4j
- Rnn : Recurrent Library for Torch7
- Software Frameworks for Deep Learning at Scale
- Trust, but Verify: Dangers of Maas. Data Fest Siberia² 2019
- Deep Learning FAQ Arcgis Pro 2.5 | Arcgis Pro 2.6 | Arcgis Pro 2.7 Version 1.1 – December 2020
- How Pytorch Optimizes Deep Learning Computations
- Chris Basoglu Partner Dev Manager
- Machine Learning Parallelism Could Be Adaptive, Composable and Automated
- CNTK) • Summary and Outlook
- DLL: a Blazing Fast Deep Neural Network Library
- Cvflow: Open Workflow for Computer Vision
- Apache Mxnet | Amazon Strategy
- On Github Since Jan 2016 Under MIT License • Python Support Since Oct 2016 (Beta), Rebranded As “Cognitive Toolkit” • External Contributions E.G
- Security Risks in Deep Learning Implementations
- Torch7 and Not So Deep) Machine Learning
- Choosing a Deep Learning Library
- Memory Optimizations Toward Training Trillion Parameter Models
- Symbolic Techniques for Deep Learning: Challenges and Opportunities Abstract
- BAGUA: Scaling up Distributed Learning with System Relaxations
- Tensorflow, Pytorch, Keras, and Horovod Huihuo Zheng Data Science Group [email protected]
- Paper, If Not Stated Otherwise, the Values Are Given for the Following Set of Parameters: P = W = 64, H = 16, I = P ⋅ H = 1024, B = 8, J = K = 512
- NVIDIA GPU CLOUD DEEP LEARNING FRAMEWORKS a Guide to the Optimized Framework Containers on NVIDIA GPU Cloud Introduction
- Scalable Distributed Deep Learning on Modern HPC Systems
- DEEP LEARNING Alison B Lowndes Deep Learning Solutions Architect & Community Manager | EMEA the BIG BANG in MACHINE LEARNING
- Deepspeed Release 0.3.0
- A Beginner's Torch7 Tutorial
- Presentation Title to Be Placed Here
- Introduction to Tensorflow Dr
- Scaling DL Training Workloads with the Cray PE Plugin Luiz Derose Sr
- NVIDIA GPU CLOUD DEEP LEARNING SOFTWARE a Guide to the Optimized Deep Learning Containers Available from NVIDIA GPU Cloud Introduction
- AI Generated Video Annotation MSC INDIVIDUAL PROJECT FINAL REPORT
- Deep Dive on Deep Learning
- Introduction to Pytorch
- Scaling Deep Learning Applications on Summit
- Zero-Offload: Democratizing Billion-Scale Model Training
- Tensorflow Tutorial, CME 323, 4 12 2018.Pdf
- Spotnik: Designing Distributed Machine Learning for Transient Cloud Resources
- Introduction to Deep Learning with Pytorch
- Arxiv:2008.04175V1 [Cs.LG] 10 Aug 2020 Sieadaawl 06 Sdagahbsdapoc.Teu the Approach
- Machine Learning and Deep Learning Frameworks and Libraries for Large-Scale Data Mining: a Survey
- Pytorch: an Imperative Style, High-Performance Deep Learning Library
- Introduction to Deep Learning with Pytorch
- UPDATE (March 2021) Topic: Training
- An Introduction to the Lua Programming Language
- MPI, PGAS, Etc.) Memcached, Dask, Etc.)
- Benchmarking Deep Learning Frameworks: Design Considerations, Metrics and Beyond
- Transparent Gradient Aggregation in Machine Learning Systems
- Tensorflow Tutorial
- Best Practice Guide
- AWS Deep Learning Containers Developer Guide AWS Deep Learning Containers Developer Guide
- Torch7: a Matlab-Like Environment for Machine Learning
- Demystifying Deep Learning Frameworks- a Comparative Analysis
- DEEP LEARNING TOOLS and FRAMEWORKS
- Software Libraries and Middleware for Exascale Systems
- Machine Learning: the First Salvo of the AI Business Revolution
- A Comparative Measurement Study of Deep Learning As a Service Framework
- Deep Learning Frameworks with Spark and Gpus Abstract
- From Research to Production with Pytorch 1.0
- Comparative Analysis of Pytorch and Caffe Frameworks
- Introduction to Lua and Torch
- Pytorch 101 Deep Learning Phd Course 2017/2018
- What Do Programmers Discuss About Deep Learning Frameworks
- TORCH: a Powerful Machine Learning Development System
- Download Apache Mxnet Tutorial
- Torch (Lua) Nn Nngraph
- Microsoft Cognitive Toolkit Outline
- Pytorch Main Functionalities
- Multi GPU Training
- Introduction to Machine Learning Deep Learning Applications