Last updated 5/2018
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.89 GB | Duration: 14h 20m
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
Homepage
https://www.udemy.com/course/intro-to-tensorflow-for-ios-android/
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