Transcription of Introduction to Deep Learning with TensorFlow
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Introduction to Deep Learning with TensorFlow
Jian Short Course 4/16/2021 Introduction to Deep Learning with TensorFlowPart ISetting up a working environment (15 mins)Part III Introduction to TensorFlow (60 mins)Part II Introduction to Deep Learning (60 mins)03 01 02 Introduction to Deep Learning with TensorFlowQ&A(5 mins/part)Part I. Working EnvironmentHPRC Portal* VPN is required for off-campus HPRC Portal (Terra)Terra Shell Access - ITerra Shell Access - IIPython Virtual Environment (VENV)Create a VENVI nstall Python ModulesActivate the VENV Deactivate (Optional)Load Modules# clean up and load Anacondacd $SCRATCH module purgemodule load # create a Python virtual environment python -m venv mylab # activate the virtual environmentsource mylab/bin/activate# install required package to be used in the portalpip install --upgrade pip setuptoolspip install jupyterlab TensorFlow sklearn matplotlib# deactivate the virtual environment# source deactivateCheck out Exercises# git clone (check out)
TensorFlow, Keras, and PyTorch Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It was developed with a focus on enabling fast experimentation. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem to
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