Deep Learning with Tensorflow and Angular 2!

Course Curriculum

Chapter 1: Intro to Android Studio

Lecture 1: Intro and Topics List

Lecture 2: Downloading and Installing Android Studio

Lecture 3: Exploring Interface

Lecture 4: Setting up an Emulator and Running Project

Lecture 5: Source Code

Chapter 2: Intro to Java

Lecture 1: Intro to Language Basics

Lecture 2: Variable Types

Lecture 3: Operations on Variables

Lecture 4: Array and Lists

Lecture 5: Array and List Operations

Lecture 6: If and Switch Statements

Lecture 7: While Loops

Lecture 8: For Loops

Lecture 9: Functions Intro

Lecture 10: Parameters and Return Values

Lecture 11: Classes and Objects Intro

Lecture 12: Superclass and Subclasses

Lecture 13: Static Variables and Axis Modifiers

Chapter 3: Intro to App Development

Lecture 1: Intro To Android App Development

Lecture 2: Building Basic UI

Lecture 3: Connecting UI to Backend

Lecture 4: Implementing Backend and Tidying UI

Chapter 4: Intro to ML Concepts

Lecture 1: Intro to ML

Lecture 2: Pycharm_Files

Chapter 5: Introduction to PyCharm for Python

Lecture 1: Intro and Topics List

Lecture 2: Downloading and Installing Pycharm and Python

Lecture 3: Exploring the Pycharm Interface

Lecture 4: Support for Python Problems or Questions

Lecture 5: Learning Python with Mammoth Interactive

Chapter 6: Python Language Basics

Lecture 1: Intro to Variables

Lecture 2: Variables Operations and Conversions

Lecture 3: Collection Types

Lecture 4: Collections Operations

Lecture 5: Control Flow If Statements

Lecture 6: While and For Loops

Lecture 7: Functions

Lecture 8: Classes and Objects

Chapter 7: Intro to Tensorflow

Lecture 1: Intro

Lecture 2: Topics List

Lecture 3: Installing TensorFlow

Lecture 4: Importing Tensorflow to Pycharm

Lecture 5: Constant Nodes and Sessions

Lecture 6: Constant Nodes and Sessions Part 2

Lecture 7: Variable Nodes

Lecture 8: Placeholder Nodes

Lecture 9: Operation nodes

Lecture 10: Loss, Optimizers, and Training

Lecture 11: Building a Linear Regression Model

Lecture 12: Source Files

Chapter 8: Machine Learning in Android Studio Projects

Lecture 1: Coming Up – Machine Learning in Android Studio Projects

Chapter 9: Tensorflow Estimator

Lecture 1: Introduction

Lecture 2: Topics List

Lecture 3: Setting up Prebuilt Estimator Model

Lecture 4: Evaluating and Predicting with Prebuilt Model

Lecture 5: Building Custom Estimator Function

Lecture 6: Testing the Custom Estimator Function

Lecture 7: Summary and Model Comparison

Lecture 8: Source Files

Chapter 10: Intro to Android Machine Learning Model Import

Lecture 1: Intro and Demo

Lecture 2: Topics List

Lecture 3: Formatting and Saving the Model

Lecture 4: Saving the Optimized Graph File

Lecture 5: Starting Android Project

Lecture 6: Building the UI

Lecture 7: Implementing Inference Functionality

Lecture 8: Testing and Error Fixing

Lecture 9: Source Files

Chapter 11: Simple MNIST

Lecture 1: Intro and Demo

Lecture 2: Topics List and Intro to MNIST Data

Lecture 3: Building Computational Graph

Lecture 4: Training and Testing the Model

Lecture 5: Saving and Freezing the Graph for Android Import

Lecture 6: Setting up Android Studio Project

Lecture 7: Building the UI

Lecture 8: Loading Digit Images

Lecture 9: Formatting Image Data

Lecture 10: Making Prediction Using Model

Lecture 11: Displaying Results and Summary

Lecture 12: Simple MNIST – Mammoth Interactive

Chapter 12: MNIST with Estimator

Lecture 1: Introduction

Lecture 2: Topics List

Lecture 3: Building Custom Estimator Function

Lecture 4: Building Input Functions, Training, and Testing

Lecture 5: Predicting Using Our Model and Model Comparisons

Lecture 6: MNIST With Estimator – Mammoth Interactive

Chapter 13: Advanced MNIST

Lecture 1: Intro and Demo

Lecture 2: Topics List