Getting started with adding layers & forward functions to your neural network in PyTorch

Defining your neural network is an art and science together. You must know the following to be the successful: 1: How to manage your input data requirement through a network of input, output and hidden layers 2: How to write the forward function to process your input data to extract signals from it

This Deep Learning Workshop #2 covers the following:

• Creating your very Network Model with input, output and hidden layers and forward function
• Understanding input data features to setup correct Network Model
• Setting network model definition and forward functions to meet the data need
• Various structured and unstructured data based network design and coding

GitHub notebook for this workshop: https://github.com/prodramp/DeepWorks/blob/main/PyTorchTutorials/02_NeuralNetworkModel.ipynb

▬▬▬▬▬▬ ⏰ WORKSHOP CONTENT TIME STAMPS ⏰ ▬▬▬▬▬▬

• (00:00) Workshop #2 Introduction
• (00:10) Topics in Workshop #2
• (01:50) What you will learn in this workshop?
• (02:43) RECAP from Workshop #1
• (03:37) Workshop #2 Kickoff
• (04:20) Using nn.Module in Python
• (05:20) Defining base neural network model
• (06:46) Design of your neural network class
• (07:20) Neural network class based on data input
• (09:22) Neural network shape
• (10:16) Model and Data Integration
• (12:52) Network with input and output layer
• (15:30) Network with 1 hidden layer
• (18:50) Network with multiple hidden layers
• (22:28) Multilayered Network Model
• (24:00) Role of Forward function in network
• (27:05) CNN Explorer Intro
• (33:10) Complex Forward Function
• (36:40) Heart Disease Problem network model
• (41:56). MNIST digits recognition problem model
• (44:15) nn.Parameters in PyTorch
• (48:30) Your Homework
• (48:50) Push notebook to GitHub
• (49:15) RECAP
• (50:40) Workshop #3 Agenda

Please visit:

• Prodramp LLC | https://prodramp.com | @prodramp
• https://www.linkedin.com/company/prodramp

Content Creator: Avkash Chauhan (@avkashchauhan)

• https://www.linkedin.com/in/avkashchauhan

Tags: #python #pytorch #ml #ai #aicloud #h2oai #driverlessai #machinelearning #cloud #mlops #model #collaboration #deeplearning #modelserving #modeldeployment #keras #tensorflow #pytorch #datarobot #datahub #aiplatform #aicloud #modelperformance #modelfit #modeleffect #modelimpact #modelbias #modeldeployment #modelregistery #modelpipeline #neptuneai #streamlit #pythonapps #deepchecks #modeltesting #codeartifact #dataartifact #modelartifact #onnx #aws #supervisor #supervisord #kaggle #keplergl #mapbox #lightgbm #xgboost #classification #regression #dataengineering #pandas #keras #tensorflow #tensorboard #mnist #cnn #convnet #alexnet #prodramp #avkashchauhan #cnnexplainer #gnn #graph #graphneuralnetwork #pyg #networkx ... https://www.youtube.com/watch?v=GDWBxSOYGwo