Machine Learning for Apps

4k learners

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.

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  • 1-year e-learning access

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Course Overview

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.

Course Outline

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- Part 1
Building - Visualizing a CNN using Sequential- Part 2
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

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