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Introduction to Machine Learning + Software

• An interview with your instructor
• Intro to the Course (9:56)
• Update! Resources Folder

Intro to Android Studio

• Intro and Topics List (2:25)
• Downloading and Installing Android Studio (6:44)
• Exploring Interface (12:12)
• Setting up an Emulator and Running Project (6:43)

Intro to Java

• Intro to Language Basics (2:46)
• Variable Types (14:00)
• Operations on Variables (10:49)
• Array and Lists (9:26)
• Array and List Operations (7:59)
• If and Switch Statements (11:34)
• While Loops (10:09)
• For Loops (8:51)
• Functions Intro (8:39)
• Parameters and Return Values (7:05)
• Classes and Objects Intro (12:13)
• Superclass and Subclasses (11:42)
• Static Variables and Axis Modifiers (7:27)

Intro to App Development

• Intro to Android App Development (1:57)
• Building Basic User Interface (12:15)
• Connecting UI to Backend (6:12)
• Implementing Backend and Tidying UI (9:09)

Intro to Machine Learning Concepts

• Introduction to ML Concepts
• Downloading and Installing PyCharm and Python (6:55)
• Exploring PyCharm (7:48)

Python Language Basics

• Intro and Topics List (2:40)
• Intro to Variables (13:17)
• Variables Operations and Conversions (12:35)
• Collection Types (12:47)
• Collections Operations (8:42)
• Control Flow If Statements (12:50)
• While and For Loops (10:44)
• Functions (11:23)
• Classes and Objects (15:40)
• Source Code

Intro to TensorFlow

• TensorFlow Intro (2:53)
• Topics List (6:09)
• Importing TensorFlow to PyCharm (4:25)
• Constant Nodes and Sessions (9:01)
• Variable Nodes (10:45)
• Placeholder Nodes (7:35)
• Operation Nodes (12:47)
• Loss, Optimizers, and Training (11:56)
• Building a Linear Regression Model (20:30)
• Source Code

Machine Learning in Android Studio Projects

• Introduction to Level 2 (5:15)

Introduction to Tensorflow Estimator

• Introduction (3:08)
• Topics List (4:12)
• Setting up Prebuilt Estimator Model (15:15)
• Evaluating and Predicting with Prebuilt Model (7:42)
• Building Custom Estimator Function (10:12)
• Testing Custom Estimator Function (7:00)
• Summary and Model Comparison (9:46)
• Source Code

Intro to Android ML Model Import

• Intro and Demo (4:09)
• Topics List (4:22)
• Formatting and Saving Model (8:25)
• Saving Optimized Graph File (14:48)
• Starting Android Project (9:01)
• Building UI (14:56)
• Implementing Inference Functionality (9:14)
• Testing and Error Fixing (11:01)
• Source Files

Simple MNIST

• Intro and Demo (3:50)
• Topics List and Intro to MNIST Data (10:24)
• Building Computational Graph (14:20)
• Training and Testing Model (14:24)
• Saving and Freezing Graph for Android Import (12:33)
• Setting up Android Studio Project (13:07)
• Building User Interface (15:58)
• Loading Digit Images (10:02)
• Formatting Image Data (10:59)
• Making Prediction Using Model (7:32)
• Displaying Results and Summary (13:13)
• Source Files

MNIST With Estimator

• Introduction (3:08)
• Topics List (2:38)
• Building Custom Estimator Function (15:34)
• Building Input Functions, Training, and Testing (13:38)
• Predicting Using Model and Model Comparisons (9:37)
• Source Files

Build Image Recognition Apps

• Introduction to Building Image Recognition Apps (6:34)

Weather Prediction

• Intro and Demo (3:49)
• Tasks List (4:36)
• Retrieving the Data (14:00)
• Formatting Data Sets (14:02)
• Building Computational Graph (11:47)
• Writing, Training, Testing, and Evaluating Functions (12:24)
• Training, Testing, and Freezing the Model (9:48)
• Setting up Android Project (8:05)
• Building the UI (15:29)
• Build App Backend and Project Summary (13:46)
• Source Code

Text Prediction

• Intro and Demo (4:13)
• Tasks List (3:17)
• Processing Text Data (13:18)
• Building Data Sets and Model Builder Function (16:16)
• Building Computational Graph (8:37)
• Writing, Training, and Testing Code (15:11)
• Training, Testing, and Freezing Graph (12:27)
• Setting up Android Project (7:41)
• Setting up UI (5:19)
• Setting up Vocab Dictionary (8:34)
• Formatting Input and Running Through Model (7:55)
• Source Code

Stock Market Prediction

• Intro and Demo (3:47)
• Task List (5:17)
• Retrieving Data via RESTful API Call (16:30)
• Parsing JSON Data Pycharm Style (6:37)
• Formatting Data (15:45)
• Building the Model (13:26)
• Training and Testing the Model (9:54)
• Freezing Graph (10:06)
• Setting up Android Project (6:07)
• Building UI (8:25)
• Requesting Data Via AsyncTask (8:25)
• Parsing JSON Data Android Style (12:04)
• Running Inference and Displaying Results (17:42)
• Source Code

Image Analysis with Keras

• Introduction to Level 4 (9:44)

Simple CIFAR-10

• Intro and Demo (4:47)
• Topics List (3:47)
• Exploring CIFAR-10 Dataset (10:48)
• Update! CIFAR_10 Android Fix
• Formatting Input Data (13:13)
• Building the Model (16:24)
• Freezing Graph and Training Model (16:56)
• Setting up the Android Project (16:43)
• Setting up UI (9:02)
• Loading and Displaying Image (6:33)
• Formatting Image Data for Model Input (13:55)
• Predicting and Displaying Results (13:26)
• Summary and Outro (6:39)
• Source Code

Face Detection

• Intro and Demo (3:20)
• Tasks List (3:09)
• Loading Face and Non Face Images (15:56)
• Reformatting Input Data (11:12)
• Build Model + Write, Train & Test Scripts (19:12)
• Freeze Graph + Train & Test Model (14:38)
• Setting up Android Project (11:49)
• Setting up UI (7:52)
• Loading and Display Images (10:11)
• Formatting Data and Running Inference (12:47)
• Displaying Results and Summary (8:51)
• Source Code

Emotions Detection

• Intro and Demo (3:39)
• Tasks List (2:34)
• Loading and Formatting Data (11:13)
• Build Training and Testing Datasets (6:52)
• Building the Model (9:57)
• Build Functions to Train, Test, & Predict (11:58)
• Training and Testing the Model (11:06)
• Setting up Android Project (6:33)
• Importing and Displaying Images (6:25)
• Convert Images and Run Inference (8:17)
• Displaying Results and Summary (7:48)
• Source Code

Increase Efficiency of Machine Learning Models

• Intro to Increasing ML Efficiency (5:47)
• Source Code

Introduction to Tensorflow Lite

• Tensorflow Lite (10:19)

Text Summarizer

• Introduction (6:22)
• How a Model Is Built (13:08)
• Training and Summarizing Mechanisms (9:31)
• Training and Summarizing Code (7:44)
• Testing the Model (5:27)
• Source Code

Object Localization

• Introduction (4:13)
• Examining Project Code (15:05)
• Testing with a Mobile Device (7:30)

Object Recognition

• Introduction (7:30)
• Examining Code (22:29)
• Testing on Mobile Device (5:36)

Intro to Tensorboard

• Introduction (2:55)
• Examining Computational Graph In Tensorboard (13:46)
• Analyzing Scalars and Histograms (13:01)
• Modifying Model Parameters Across Multiple Runs (10:32)
• Source Code

Advanced ML Concepts

• Introduction (18:49)
• Source Code

Advanced MNIST

• Intro and Demo (3:42)
• Topics List (3:41)
• Building Neuron Functions (11:18)
• Building the Convolutional Layers (11:51)
• Building Dense, Dropout, and Readout Layers (14:38)
• Loss & Optimizer Functions, Training, & Testing (19:51)
• Optimizing Saved Graph (10:57)
• Setting up Android Project (12:30)
• Setting Up UI (10:58)
• Load and Display Digit Images (6:14)
• Formatting Model Input (13:52)
• Displaying Results and Summary (11:11)
• Source Files

Advanced CIFAR-100

• Intro and Demo (3:18)
• Tasks List (3:11)
• Inputting and Formatting Data (10:50)
• Building the Model (10:19)
• Training, Testing, and Freezing Model (10:57)
• Setting up Android Project (10:24)
• Building UI (8:09)
• Loading and Displaying Images (7:03)
• Converting Image Data & Running Inference (7:37)
• Summary and Outro (9:29)
• Source Code

Image Recognition in iOS

• Introduction and Demo (3:20)
• Project Setup (6:59)
• Displaying and Resizing Images (9:42)
• Converting Image to Pixel Buffer (14:06)
• Summary and Outro (8:07)
• Source Code

Intro to iOS

• Introduction (2:15)
• Source Code

Xcode Intro

• Downloading and Installing (6:22)
• Exploring XCode’s Interface (15:40)

Swift Language Basics

• Variables Intro (7:57)
• Variable Operations (10:43)
• Collections (8:57)
• Control Flow (10:18)
• Functions (5:28)
• Classes and Objects (9:55)

iOS App Development Intro

• Building App From Start to Finish (12:46)

Intro to CoreML

• Introduction to CoreML (9:08)

iOS Tensorflow Model Import

• Introduction (4:35)
• Converting pb to mlmodel
• File & Setting up Project (7:34)
• Running Inference Through Model (9:58)
• Testing and Summary (3:55)

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