Make predictions with Python machine learning for apps

Course Curriculum

Chapter 1: Resources

Lecture 1: Resources

Chapter 2: Intro to Android Studio

Lecture 1: Intro to Android and Project Outline

Lecture 2: Downloading and Installing Android Studio

Lecture 3: Exploring Interface

Lecture 4: Setting up Emulator and Running Project

Chapter 3: Intro to Java

Lecture 1: Java Language Basics

Lecture 2: Variable Types

Lecture 3: Operations on Variables

Lecture 4: Arrays and Lists

Lecture 5: Array and List Operations

Lecture 6: If Statements and Switch Statements

Lecture 7: While Loops

Lecture 8: For Loops

Lecture 9: Functions

Lecture 10: Parameters and Return Values

Lecture 11: Classes and Objects

Lecture 12: Superclass and Subclasses

Lecture 13: Static Variables and Axis Modifiers

Chapter 4: ————-App Development————-

Lecture 1: Android App Development

Lecture 2: Building Basic User Interface

Lecture 3: Connecting UI to Backend

Lecture 4: Implementing Backend and Tidying UI

Chapter 5: Machine Learning Concepts

Lecture 1: ML Concepts Introduction

Lecture 2: Intro to PyCharm and Project Outline

Lecture 3: How to Install PyCharm and Python

Lecture 4: Let's Explore PyCharm

Lecture 5: (Files) Source Code

Chapter 6: Python Language Basics

Lecture 1: Variables

Lecture 2: Variable Operations and Conversions

Lecture 3: Collection Types

Lecture 4: Operations on Collections

Lecture 5: Control Flow: If Statements

Lecture 6: While and For Loops

Lecture 7: Functions

Lecture 8: Classes and Objects

Lecture 9: (Files) Source Code

Chapter 7: TensorFlow

Lecture 1: TensorFlow Introduction

Lecture 2: Project Outline

Lecture 3: How to Import TensorFlow to PyCharm

Lecture 4: Constant Nodes and Sessions

Lecture 5: Variable Nodes

Lecture 6: Placeholder Nodes

Lecture 7: Operation Nodes

Lecture 8: Loss, Optimizers, and Training

Lecture 9: Building a Linear Regression Model

Lecture 10: (Files) Source Code

Chapter 8: ————-Machine Learning in Android Studio Projects————-

Lecture 1: Introduction to ML for Android

Chapter 9: TensorFlow Estimator

Lecture 1: TensorFlow Estimator Introduction

Lecture 2: Project Outline

Lecture 3: Setting up Prebuilt Estimator Model

Lecture 4: Evaluating and Predicting with Model

Lecture 5: Building Custom Estimator Function

Lecture 6: Testing Custom Estimator Function

Lecture 7: Summary and Model Comparison

Lecture 8: (Files) Source Code

Chapter 10: Importing Android Machine Learning Model

Lecture 1: Intro & Demo: ML Model Import

Lecture 2: Project Outline

Lecture 3: Formatting and Saving Model

Lecture 4: Saving Optimized Graph File

Lecture 5: Starting Android Project

Lecture 6: Building UI

Lecture 7: Implementing Inference Functionality

Lecture 8: Testing and Error Handling

Lecture 9: (Files) Source Code

Chapter 11: Simple MNIST

Lecture 1: Intro & Demo: Simple MNIST

Lecture 2: Project Outline and Intro to MNIST Data

Lecture 3: Building Computational Graph

Lecture 4: Training and Testing Model

Lecture 5: Saving Graph for Android Import

Lecture 6: Setting up Android Studio Project

Lecture 7: Building User Interface

Lecture 8: Loading Digit Images

Lecture 9: Formatting Image Data

Lecture 10: Making Prediction Using Model

Lecture 11: Displaying Results and Summary

Lecture 12: (Files) Source Code

Chapter 12: MNIST with Estimator

Lecture 1: MNIST With Estimator Introduction

Lecture 2: Project Outline

Lecture 3: Building Custom Estimator Function

Lecture 4: Training & Testing Input Functions

Lecture 5: Predicting Using Model & Comparisons

Lecture 6: (Files) Source Code

Chapter 13: ————-Build Image Recognition Apps————-

Lecture 1: Introduction to Image Recognition Apps

Chapter 14: Weather Prediction

Lecture 1: Intro and Demo: Weather Prediction

Lecture 2: Project Outline

Lecture 3: Retrieving Data