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https://github.com/darsnack/ece901project

A repository containing code and reports for UW-Madison ECE901: Large-Scale Machine Learning

https://github.com/darsnack/ece901project

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

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    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
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    DOI references
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    Scientific vocabulary similarity
    Low similarity (10.4%) to scientific vocabulary
Last synced: 6 months ago · JSON representation

Repository

A repository containing code and reports for UW-Madison ECE901: Large-Scale Machine Learning

Basic Info
  • Host: GitHub
  • Owner: darsnack
  • Language: Verilog
  • Default Branch: master
  • Size: 4.79 MB
Statistics
  • Stars: 0
  • Watchers: 0
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Created over 9 years ago · Last pushed about 9 years ago
Metadata Files
Readme

README.md

ECE901Project

A repository containing code and reports for UW-Madison ECE901: Large-Scale Machine Learning

Setup

Make sure you are running Python 3.5.

Also, run the following commands in conda environment to update TF to the latest version. shell (tensorflow) $ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-0.12.0rc0-py3-none-any.whl (tensorflow) $ pip install --ignore-installed --upgrade $TF_BINARY_URL

Structure

Hardware - VGGNet-16: Contains the Vivado project for FPGA implementation.

LaTeXStyleFiles: Contains LaTeX style files that may need to be installed on your system to compile LaTeX source.

PaperPresentation: Contains LaTeX source for paper presentation assignment.

ProjectProposal: Contains LaTeX source for project proposal assignment.

ProposalPresentation: Contains LaTeX source for project proposal presentation.

Tensorflow - TFMechanics101Tutorial: Contains source code for TF tutorial (https://www.tensorflow.org/versions/master/tutorials/mnist/tf/index.html) - fullyconnectedfeed.py: Run this using python fully_connected_feed.py to train the network. - inputdata.py: Just for reference. The training code pulls this file in via import. - _mnist.py: Just for reference. The training code pulls this file in via import. - TFCNNTutorial: Contains source code for TF CNN tutorial (https://www.tensorflow.org/versions/master/tutorials/deepcnn/index.html) - _cifar10.py: Just for reference. The training code pulls this file in via import. - cifar10input.py: Just for reference. The model code pulls this file in via import. - _cifar10train.py: Run this using `python cifar10train.pyto train the network. - _TwoLayerCNN_: Contains source code for CPU implementation of custom two layer CNN. - _model.py_: Contains the model related functions likeinference(),loss(), andtrain()`.

Owner

  • Name: Kyle Daruwalla
  • Login: darsnack
  • Kind: user
  • Location: Cold Spring Harbor Lab, NY

NeuroAI scholar at CSHL

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