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Oreilly - Machine Learning for Apps - 80000SREDL06
Oreilly - Machine Learning for Apps
by Devslopes | Released October 2018 | ISBN: None


Welcome to the most comprehensive course on Core ML, one of Apples hot new features for iOS 11. The goal with Machine Learning is to mimic the human mind. It can be used to identify things like objects or images, make predictions and even analyze and identify speech. Dive in and learn the core concepts of machine learning and start building apps that can think! In this course you going to learn everything you need to know to start building more intelligent apps and your own ML Models. If you have basic experience with iOS or mobile development then take this course Show and hide more Publisher Resources Download Example Code
  1. Intro to Course
    • What is Machine Learning? 00:07:32
    • Basics of Machine Learning 00:06:17
    • Installing Anaconda / Python Environment 00:07:03
    • Downloading / Setting Up Atom & Plugins 00:08:44
  2. Python Basics
    • Variables in Python 00:08:07
    • Functions, Conditionals, & Loops in Python 00:09:34
    • Arrays & Tuples in Python 00:13:35
    • Importing Modules in Python 00:05:05
  3. Building a Classification Model
    • What is scikit-learn? Why use it? 00:03:35
    • Installing scikit-learn & scipy with Anaconda 00:03:11
    • Intro to the Iris Dataset 00:03:11
    • Datasets: Features & Labels Explained 00:07:22
    • Loading the Iris Dataset / Examining & Preparing Data 00:09:10
    • Creating / Training a KNeighborsClassifier 00:09:25
    • Testing Prediction Accuracy with Test Data 00:11:48
    • Building Our Own KNeighborsClassifier 00:17:43
  4. Building a Convolutional Neural Network
    • What is Keras? Why use it? 00:07:44
    • What is a Convolutional Neural Network (CNN)? 00:26:13
    • Installing Keras with Anaconda 00:04:21
    • Preparing Dataset for a CNN 00:17:21
    • Building / Visualizing a CNN using Sequential: Part 1 00:13:50
    • Building / Visualizing a CNN using Sequential: Part 2 00:19:24
    • Training CNN / Evaluating Accuracy / Saving to Disk 00:17:36
    • Switching Python Environments / Converting to Core ML Model 00:13:22
  5. Building a Handwriting Recognition App
    • Intro to App – Handwriting 00:02:39
    • Building Interface / Wiring Up 00:11:26
    • Drawing On Screen 00:20:44
    • Importing Core ML Model / Reading Metadata 00:04:59
    • Utilizing Core ML / Vision to Make Prediction 00:17:14
    • Handling / Displaying Prediction Results 00:14:54
  6. Core ML Basics
    • Intro to App – Core ML Photo Analysis 00:04:08
    • What is Machine Learning? 00:07:31
    • What is Core ML? 00:04:48
    • Creating Xcode Project 00:02:26
    • Building ImageVC in Interface Builder / Wiring Up 00:07:23
    • Creating ImageCell & Subclass / Wiring Up 00:07:56
    • Creating FoodItems Helper File 00:06:45
    • Creating Custom 3x3 Grid UICollectionViewFlowLayout 00:08:55
    • Choosing, Downloading, Importing Core ML Model 00:05:04
    • Passing Images Through Core ML Model 00:12:02
    • Handling Core ML Prediction Results 00:09:25
    • Challenge – Core ML Photo Analysis 00:01:00
  7. Show and hide more

    Oreilly - Machine Learning for Apps


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