Intro to Course
  • What is Machine Learning?
  • Basics of Machine Learning
  • Installing Anaconda / Python Environment
  • Downloading / Setting Up Atom & Plugins
Python Basics
  • Variables in Python
  • Functions, Conditionals, & Loops in Python
  • Arrays & Tuples in Python
  • Importing Modules in Python
Building a Classification Model
  • What is scikit-learn? Why use it?
  • Installing scikit-learn & scipy with Anaconda
  • Intro to the Iris Dataset
  • Datasets: Features & Labels Explained
  • Loading the Iris Dataset / Examining & Preparing Data
  • Creating / Training a KNeighborsClassifier
  • Testing Prediction Accuracy with Test Data
  • Building Our Own KNeighborsClassifier
Building a Convolutional Neural Network
  • What is Keras? Why use it?
  • What is a Convolutional Neural Network (CNN)?
  • Installing Keras with Anaconda
  • Preparing Dataset for a CNN
  • Building / Visualizing a CNN using Sequential: Part 1
  • Building / Visualizing a CNN using Sequential: Part 2
  • Training CNN / Evaluating Accuracy / Saving to Disk
  • Switching Python Environments / Converting to Core ML Model
Building a Handwriting Recognition App
  • Intro to App – Handwriting
  • Building Interface / Wiring Up
  • Drawing On Screen
  • Importing Core ML Model / Reading Metadata
  • Utilizing Core ML / Vision to Make Prediction
  • Handling / Displaying Prediction Results
Core ML Basics
  • Intro to App – Core ML Photo Analysis
  • What is Machine Learning?
  • What is Core ML?
  • Creating Xcode Project
  • Building ImageVC in Interface Builder / Wiring Up
  • Creating ImageCell & Subclass / Wiring Up
  • Creating FoodItems Helper File
  • Creating Custom 3x3 Grid UICollectionViewFlowLayout
  • Choosing, Downloading, Importing Core ML Model
  • Passing Images Through Core ML Model
  • Handling Core ML Prediction Results
  • Challenge – Core ML Photo Analysis