Introduction
  • Introduction
  • Agenda, myths and latest applications of machine intelligence (MI)
Intro to Machine Learning in EDA/CAD and frameworks
  • MI in design automation and MI categories
  • MI architecture and LIVE QnA with participants
  • MI foundation and steps to add colaboratory lab for python programming
  • Introduction to python scripting
  • Quick QnA session with tensor flow
  • LIVE QnA with participants regarding tensor flow
Wire resistance estimation using regression model
  • Regression model, wire resistance estimation and dataset normalization
  • ML model, loss function and gradient descent learning algorithm
  • LIVE QnA and labs on gradient descent algorithm
  • ML solution flow and resistance estimation with linear regression labs
  • Training model for resistance estimation with linear regression
Error Analysis
  • Predicting resistance values and error analysis
  • LIVE QnA on regression and resistance estimation
  • Wire error model and underfitting concept
  • LIVE QnA on wire error model and underfitting
  • Million dollar query on parasitics extraction
Wire Capacitance Estimation (WiCE)
  • Wire capacitance estimation (WiCE), loss function and labs
  • WiCE labs and exercise description
  • LIVE QnA with participants on WiCE
Cell classification
  • Classification examples, algorithms and decision boundary
  • VLSI cell classification (VCC) and data-set
  • Logistic regression, VCC machine learning model and VCC loss function
  • Labs on binary classification of cells using logistic regression
  • Confusion matrix
Conclusion
  • Support vector machine algorithm and conclusion