Intro To Tensorflow - For Ios & Android

Learn artificial intelligence, machine learning & coding. Build projects! Explore Python, Java, PyCharm, databases, more

What you'll learn
Learn everything with examples and practical projects
Explore machine learning concepts
Learn how to use TensorFlow 1.4.1 to build, train, and test machine learning models
We explore Python 3.6.2 and Java 8 languages
Use PyCharm 2017.2.3 and Android Studio 3 to build apps.
Intro to iOS, Xcode, Swift, Core ML, and image recognition
Requirements
No experience required!
We will take you through the steps of downloading and installing Android Studio, PyCharm, and Python
Description
This course was funded by a wildly successful Kickstarter

Explore PyCharm 2017.2.3 and the amazing Python 3.6.2 language
Explore Android Studio 3 and the Java 8 language
Discover applications of machine learning and where we use artificial intelligence and algorithms daily
Learn what TensorFlow 1.4.1 is and how it makes machine learning development easier
Build a linear regression model to fit a line through data
Learn how to incorporate machine learning models into Android apps
Build a simple digit recognition project using the MNIST handwritten digit database
Learn how the TensorFlow estimator differs from other computational graphs

A machine learning framework for everyone

If you want to build sophisticated and intelligent mobile apps or simply want to know more about how machine learning works in a mobile environment, this course is for you.
Be one of the first
There are next to no courses on big platforms that focus on mobile machine learning in particular. All of them focus specifically on machine learning for a desktop or laptop environment.
We provide clear, concise explanations at each step along the way so that viewers can not only replicate, but also understand and expand upon what I teach. Other courses don’t do a great job of explaining exactly what is going on at each step in the process and why we choose to build models the way we do. 
No prior knowledge is required
We will teach you all you need to know about the languages, software and technologies we use. If you have lots of experience building machine learning apps, you may find this course a little slow because it’s designed for beginners.
Jump into a field that has more demand than supply

Machine learning changes everything. It’s bringing us self-driving cars, facial recognition and artificial intelligence. And the best part is: anyone can create such innovations.
Enroll now to start the next step of your career

Overview

Lecture 1 Course Trailer

Section 1: Update! Resources

Lecture 2 Update! Resources

Section 2: Intro to Android Studio

Lecture 3 Intro to Android

Lecture 4 Downloading & Installing Android Studio

Lecture 5 Exploring Interface

Lecture 6 Setting up Emulator and Running Project

Section 3: Intro to Java

Lecture 7 Java Language Basics

Lecture 8 Variable Types

Lecture 9 Operations on Variables

Lecture 10 Arrays and Lists

Lecture 11 Array and List Operations

Lecture 12 If and Switch Statements

Lecture 13 While Loops

Lecture 14 For Loops

Lecture 15 Functions Intro

Lecture 16 Parameters and Return Values

Lecture 17 Classes and Objects Intro

Lecture 18 Superclass and Subclasses

Lecture 19 Static Variables and Axis Modifiers

Section 4: Intro to App Development

Lecture 20 Intro to Android App Development

Lecture 21 Building User Interface

Lecture 22 Connecting UI to Backend

Lecture 23 Implementing Backend and Tidying UI

Section 5: Intro to Machine Learning Concepts

Lecture 24 ML Concepts Intro

Lecture 25 Intro to PyCharm

Lecture 26 Installing PyCharm and Python

Lecture 27 Exploring PyCharm

Lecture 28 (Files) Source Code

Section 6: Python Language Basics

Lecture 29 Intro to Variables

Lecture 30 Variables Operations and Conversions

Lecture 31 Collection Types

Lecture 32 Collections Operations

Lecture 33 Control Flow: If Statements

Lecture 34 While and For Loops

Lecture 35 Functions

Lecture 36 Classes and Objects

Lecture 37 (Files) Source Code

Section 7: Intro to TensorFlow

Lecture 38 TensorFlow Intro

Lecture 39 Topics List

Lecture 40 Importing TensorFlow to PyCharm

Lecture 41 Constant Nodes and Sessions

Lecture 42 Variable Nodes

Lecture 43 Placeholder Nodes

Lecture 44 Operation Nodes

Lecture 45 Loss, Optimizers, and Training

Lecture 46 Building a Linear Regression Model

Lecture 47 (Files) Source Code

Section 8: Machine Learning in Android Studio Projects

Lecture 48 Introduction to ML for Android

Section 9: Introduction to TensorFlow Estimator

Lecture 49 Introduction to TensorFlow Estimator

Lecture 50 Topics List

Lecture 51 Setting up Prebuilt Estimator Model

Lecture 52 Evaluating and Predicting with Model

Lecture 53 Building Custom Estimator Function

Lecture 54 Testing Custom Estimator Function

Lecture 55 Summary and Model Comparison

Lecture 56 Source Code

Section 10: Intro to Android ML Model Import

Lecture 57 Intro & Demo: Android ML Model Import

Lecture 58 Topics List

Lecture 59 Formatting and Saving Model

Lecture 60 Saving Optimized Graph File

Lecture 61 Starting Android Project

Lecture 62 Building UI

Lecture 63 Implementing Inference Functionality

Lecture 64 Testing and Error Fixing

Lecture 65 Source Files

Section 11: Simple MNIST

Lecture 66 Intro & Demo: Simple MNIST

Lecture 67 Topics List and Intro to MNIST Data

Lecture 68 Building Computational Graph

Lecture 69 Training and Testing Model

Lecture 70 Saving Graph for Android Import

Lecture 71 Setting up Android Studio Project

Lecture 72 Building User Interface

Lecture 73 Loading Digit Images

Lecture 74 Formatting Image Data

Lecture 75 Making Prediction Using Model

Lecture 76 Displaying Results and Summary

Lecture 77 Source Files

Section 12: MNIST With Estimator

Lecture 78 MNIST With Estimator Intro

Lecture 79 Topics List

Lecture 80 Building Custom Estimator Function

Lecture 81 Training & Testing Input Functions

Lecture 82 Predicting Using Model & Comparisons

Lecture 83 Source Files

Section 13: Xcode Intro

Lecture 84 Downloading and Installing Xcode

Lecture 85 Don't Have a Mac Computer?

Lecture 86 Exploring XCode's Interface

Section 14: Swift Language Basics

Lecture 87 Variables Intro

Lecture 88 Variables Operations

Lecture 89 Collections

Lecture 90 Control Flow

Lecture 91 Functions

Lecture 92 Classes and Objects

Section 15: iOS App Development Intro

Lecture 93 Building App From Start to Finish

Section 16: Intro to CoreML

Lecture 94 Intro to CoreML

Section 17: TensorFlow for iOS

Lecture 95 Introduction to TensorFlow for iOS

Lecture 96 Converting pb to mlmodel File and Project

Lecture 97 Running Inference Through Model

Lecture 98 Testing and Summary

Section 18: Image Recognition in iOS

Lecture 99 Intro & Demo: Image Recognition in iOS

Lecture 100 Project Setup

Lecture 101 Displaying and Resizing Images

Lecture 102 Converting Image to Pixel Buffer

Lecture 103 Summary and Outro

Lecture 104 Source Code

Section 19: Bonus

Lecture 105 Please rate this course

Lecture 106 Bonus Lecture: Newsletter

Anyone who wants to learn the technology that is revolutionizing how we interact with the world around us