AI Saturdays - AI Developers, Boise

I started a community group, AI Developers Boise and organized series of weekly workshop/presentation events (AI Saturdays) with the support of nurture.ai for the three months in Summer, 2018. Boise State University helped us with the venue for all the workshop period and here are the people without whom the event couldn’t have succeeded. :)

You can find all the covered resources and code here.

Topics Covered

• Week 0 (March 5, 2018) - AI6 Orientation
• Week 1 (March 12, 2018) [old link] [Preliminary Readings]
  • Python, Installation and Environment Setup
  • Introduction to Python
  • Numpy, Scipy and Matplotlib
• Week 2 (March 19, 2018) [old link] [Preliminary Readings]
  • Beginners level tutorial on Numpy
  • Beginners level tutorial on Pandas
  • Tutorial on Linear Regression (Naive Implementation and Intuition)
  • Linera Regression Intuition
  • Univariate Linear Regression
  • Linear regression using Matrix Multiplication
  • Linear Algebra - data generation simulation and demonstration
• Week 3 (June 2, 2018) [old link] [Preliminary Readings]
  • Titanic: Machine Learning from Disaster (Kaggle) and Logistic Regression
  • Probability Distributions
  • Data Science in Agriculture
• Week 4 (June 9, 2018) [Preliminary Readings]
  • Tensorflow, GCP and ML Engine
  • Convex Optimization (General Intuition)
  • Gradient Descent ( Naive implementation from scratch to train a simple linear regression)
• Week 5 (June 16, 2018)[Preliminary Readings]
  • Introduction to Support Vector Machines
  • Simple plots to get a glimpse of Loss Function in Logistic Regression
  • Demonstration (muffins vs cupcake classification using SVM)
• Week 6 (June 30, 2018)[Preliminary Study: CS221n Chapter 2, CS221n Chapter 3]
  • Chapter 4 - Introduction to Neural Networks
  • Chapter 5 - Convolutional Neural Networks (CNNs)
  • Notes on lecture 2 and simple code implementation of K-NN algorithm
• Week 7 (July 7, 2018)[Preliminary Readings]
  • Chapter 6, Chapter 7 - Training Neural Networks
• Week 8 (July 14, 2018)[Preliminary Readings]
  • Chapter 9 - Convolutional Neural Networks Architectures (Alexnet, Googlenet, VGGNet, etc.)
• Week 9 (July 21, 2018)[Preliminary Readings]
  • Chapter 10) - Recurrent Neural Networks (Sequence Models, eg. Long Short Term Memory networks
  • Chapter 8) - Deep Learning Frameworks (Tensorflow, PyTorch, Keras, etc.
• Week 10 (July 28, 2018)[Preliminary Readings] <– We’re here
  • Overview of concepts from Chapter 11 and Chapter 13 (Object Detection, Segmentation and Generative NN Models)
  • Project presentations on results and findings from participants
  • Concluding the first cohort of AI6 Saturdays. :)