Machine Learning for Apps

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.

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Machine Learning for Apps Training program course overview

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.

 

The registration process

Once you have completed our simplified enrolment process, you’ll receive an email confirmation with your payment receipt in your registered email ID. You can then access the entire content of the online student portal immediately by logging in to your account on our site. Should you require any assistance please reach out to us via email (support@greycampus.com) or via our online chat system.

The course curriculum

The curriculum for this Machine Learning for Apps training incorporates all updates The following is a list of broad topics covered

  • What is Machine Learning?
  • Basics of Machine Learning
  • Installing Anaconda / Python Environment
  • Downloading / Setting Up Atom & Plugins
  • Variables in Python
  • Arrays & Tuples in Python
  • Functions, Conditionals, & Loops in Python
  • Importing Modules in Python
  • What is scikit-learn- Why use it
  • Installing scikit-learn & scipy with Anaconda
  • Intro to the Iris Dataset
  • Datasets- Features & Labels Explained
  • Loading the Iris Dataset - Examining & Preparing Data
  • Creating - Training a KNeighborsClassifier
  • Testing Prediction Accuracy with Test Data
  • Building Our Own KNeighbors Classifier
  • What is Keras- Why use it
  • What is a Convolutional Neural Network (CNN)
  • Installing Keras with Anaconda
  • Preparing Dataset for a CNN
  • Building - Visualizing a CNN using Sequential
  • Training CNN - Evaluating Accuracy - Saving to Disk
  • Switching Python Environments - Converting to Core ML Model
  • Intro to App – Handwriting
  • Building Interface - Wiring Up
  • Drawing On Screen
  • Importing Core ML Model - Reading Metadata
  • Utilizing Core ML - Vision to Make Prediction
  • Handling - Displaying Prediction Results
  • Intro to App – Core ML Photo Analysis
  • What is Machine Learning
  • What is Core ML
  • Creating Xcode Project
  • Building ImageVC in Interface Builder - Wiring Up
  • Creating ImageCell & Subclass - Wiring Up
  • Creating FoodItems Helper File
  • Creating Custom 3x3 Grid UICollectionViewFlowLayout
  • Choosing, Downloading, Importing Core ML Model
  • Passing Images Through Core ML Model
  • Handling Core ML Prediction Results
  • Challenge – Core ML Photo Analysis