| Module 1 | Introduction to Course | |
|---|---|---|
| Unit 1 | What is Machine Learning? (7:31) | |
| Unit 2 | Basics of Machine Learning (6:17) | |
| Unit 3 | Installing Anaconda / Python Environment (7:02) | |
| Unit 4 | Downloading / Setting Up Atom & Plugins (8:43) | |
| Unit 5 | Source File | |
| Module 2 | Python Basics | |
| Unit 1 | Variables in Python (8:07) | |
| Unit 2 | Arrays & Tuples in Python (13:35) | |
| Unit 3 | Functions, Conditionals, & Loops in Python (9:33) | |
| Unit 4 | Importing Modules in Python (5:04) | |
| Module 3 | Building a Classification Model | |
| Unit 1 | What is scikit-learn- Why use it (3:34) | |
| Unit 2 | Installing scikit-learn & scipy with Anaconda (3:11) | |
| Unit 3 | Intro to the Iris Dataset (3:28) | |
| Unit 4 | Datasets- Features & Labels Explained (7:22) | |
| Unit 5 | Loading the Iris Dataset - Examining & Preparing Data (9:10) | |
| Unit 6 | Creating - Training a KNeighborsClassifier (9:25) | |
| Unit 7 | Testing Prediction Accuracy with Test Data (11:47) | |
| Unit 8 | Building Our Own KNeighbors Classifier (17:43) | |
| Module 4 | Building a Convolutional Neural Network | |
| Unit 1 | What is Keras- Why use it (7:44) | |
| Unit 2 | What is a Convolutional Neural Network (CNN) (26:12) | |
| Unit 3 | Installing Keras with Anaconda | |
| Unit 4 | Preparing Dataset for a CNN | |
| Unit 5 | Building - Visualizing a CNN using Sequential- Part 1 | |
| Unit 6 | Building - Visualizing a CNN using Sequential- Part 2 | |
| Unit 7 | Training CNN - Evaluating Accuracy - Saving to Disk (17:36) | |
| Unit 8 | Switching Python Environments - Converting to Core ML Model (13:21) | |
| Module 5 | Building a Handwriting Recognition App | |
| Unit 1 | Intro to App – Handwriting (2:38) | |
| Unit 2 | Building Interface - Wiring Up (11:25) | |
| Unit 3 | Drawing On Screen (20:44) | |
| Unit 4 | Importing Core ML Model - Reading Metadata (4:59) | |
| Unit 5 | Utilizing Core ML - Vision to Make Prediction (17:13) | |
| Unit 6 | Handling - Displaying Prediction Results (14:54) | |
| Module 6 | Core ML Basics | |
| Unit 1 | Intro to App – Core ML Photo Analysis | |
| Unit 2 | What is Machine Learning | |
| Unit 3 | What is Core ML (4:48) | |
| Unit 4 | Creating Xcode Project (2:26) | |
| Unit 5 | Building ImageVC in Interface Builder - Wiring Up (7:23) | |
| Unit 6 | Creating ImageCell & Subclass - Wiring Up | |
| Unit 7 | Creating FoodItems Helper File | |
| Unit 8 | Creating Custom 3x3 Grid UICollectionViewFlowLayout (8:54) | |
| Unit 9 | Choosing, Downloading, Importing Core ML Model | |
| Unit 10 | Passing Images Through Core ML Model | |
| Unit 11 | Handling Core ML Prediction Results (9:25) | |
| Unit 12 | Challenge – Core ML Photo Analysis |
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