CoreML Master Machine Learning for iOS Apps

CoreML – Master Machine Learning for iOS Apps, available at $64.99, has an average rating of 4.15, with 36 lectures, based on 134 reviews, and has 1145 subscribers.

You will learn about Build intelligent iOS apps that use machine learning. Create an app that uses the Inception V3 framework with CoreML to identify objects visually. Understand how the ImagePickerView works and how you can enable the camera functionality in your iOS apps. Make an app that recognises the name of a flower just from a picture. This course is ideal for individuals who are If you are an intermediate to advanced iOS developer looking to add more skills under your belt. or If you are looking to quickly get up to date with the latest iOS 11 APIs. or If you are a beginner and want to learn to create intelligent iOS apps using machine learning without having to understand a lot of complicated maths. It is particularly useful for If you are an intermediate to advanced iOS developer looking to add more skills under your belt. or If you are looking to quickly get up to date with the latest iOS 11 APIs. or If you are a beginner and want to learn to create intelligent iOS apps using machine learning without having to understand a lot of complicated maths.

Enroll now: CoreML – Master Machine Learning for iOS Apps

Summary

Title: CoreML – Master Machine Learning for iOS Apps

Price: $64.99

Average Rating: 4.15

Number of Lectures: 36

Number of Published Lectures: 36

Number of Curriculum Items: 36

Number of Published Curriculum Objects: 36

Original Price: $39.99

Quality Status: approved

Status: Live

What You Will Learn

Build intelligent iOS apps that use machine learning.

Create an app that uses the Inception V3 framework with CoreML to identify objects visually.

Understand how the ImagePickerView works and how you can enable the camera functionality in your iOS apps.

Make an app that recognises the name of a flower just from a picture.

Who Should Attend

If you are an intermediate to advanced iOS developer looking to add more skills under your belt.

If you are looking to quickly get up to date with the latest iOS 11 APIs.

If you are a beginner and want to learn to create intelligent iOS apps using machine learning without having to understand a lot of complicated maths.

Target Audiences

If you are an intermediate to advanced iOS developer looking to add more skills under your belt.

If you are looking to quickly get up to date with the latest iOS 11 APIs.

If you are a beginner and want to learn to create intelligent iOS apps using machine learning without having to understand a lot of complicated maths.

Have an app idea that requires machine learning?

But all the maths getting you down?

Want a simple and easy way of implementing machine learning in your iOS apps?

Then this course is for you!

Join me as we dive into Apple’s latest iOS 11 API – CoreML – a native iOS framework built with Swift.

After this course you fully understand:

What is machine learning

Supervised learning

Unsupervised learning

Reinforcement learning

How CoreML works

How to implement image recognition in your iOS apps

How to convert existing trained?models created using Caffe, Keras, TensorFlow or?scikit Learn into a MLModel that you can drag and drop into your iOS apps.

and much much more

Take a look at what other students have been saying about this course:

“I am about a third through this course and I have learned so much. This course is worth way more than what it cost but I’m thankful prices are low or I might have passed it up in the first place not knowing what I would get. I have used a couple Udemy courses and countless youtube tutorials. This is the best course I’ve ever took.” – Jeffrey Nelson

“The course offers interesting concepts coupled with a teacher that explains things clearly. You get to make a bunch of interesting apps and expand your skills. Thanks Angela!” – Megan Eding

“Clear tutorials, the lecturer explains everything well. It is one of the best courses I have participated in on Udemy.” – Mark Garcia

“Angela is connecting the missing dots for me ” – Tom Colenbrander

What are you waiting for? Join the course?today!

Course Curriculum

Chapter 1: Introduction to Machine Learning

Lecture 1: Install the Required Software

Lecture 2: Introduction to Machine Learning

Lecture 3: Supervised Learning

Lecture 4: Unsupervised Learning

Lecture 5: Reinforcement Learning

Chapter 2: Apples Latest API for iOS 11 – CoreML Framework

Lecture 1: What is CoreML?

Lecture 2: What Well Make By the End of This Module

Lecture 3: How to Import the Image Recognition Models and Enable Camera Functionality

Lecture 4: Getting Image Recognition Results Back from Our Inception V3 Model

Lecture 5: Hotdog or Not Hotdog?

Lecture 6: Download the Completed App Project

Chapter 3: Advanced CoreML – How to Convert Pre-Trained Models Using CoreML Tools

Lecture 1: What Well Make By the End of This Module

Lecture 2: Installing CoreML Tools Using Python

Lecture 3: Converting a Caffe Model in to MLModel

Lecture 4: [Challenge] Set up a UIImagePickerController

Lecture 5: [Solution] Set up a UIImagePickerController

Lecture 6: [Challenge] Getting Classifications from our Model

Lecture 7: [Solution] Getting Classifications from our Model

Lecture 8: [Challenge] Adding Cocoapods to Our Project

Lecture 9: [Solution] Adding Cocoapods to Our Project

Lecture 10: [Challenge] Making HTTP Get requests to Wikipedia using Alamofire and REST

Lecture 11: [Solution] Making HTTP Get requests to Wikipedia using Alamofire and REST

Lecture 12: [Challenge] Parsing the JSON Result using SwiftyJSON

Lecture 13: [Solution] Parsing the JSON Result using SwiftyJSON

Lecture 14: Displaying Images from a URL using SDWebImage

Lecture 15: [Bonus Lesson] Creating the App Icon from Scratch and Styling the App

Lecture 16: Download the Completed App Project

Chapter 4: [Bonus Section] Adding Machine Learning to iOS Apps Using IBM Watson

Lecture 1: What Well Make By the End of This Module

Lecture 2: A Note About RestKit

Lecture 3: How to Install and Use Carthage as a Dependency Manager

Lecture 4: The Many Ways of Installing Carthage

Lecture 5: How to Implement the Camera and Photo Library Functionality

Lecture 6: How to Use a Pre-Trained Neural Net from IBM to Classify Any Image

Lecture 7: How to Process the Data You Get Back from IBM Bluemix

Lecture 8: Lets Beautiful Our App and Make it Look like the Real Deal

Lecture 9: Download the Completed App Project

Instructors

App Brewery Co.
in-Person & Online Development Bootcamp

Rating Distribution

1 stars: 1 votes

2 stars: 3 votes

3 stars: 16 votes

4 stars: 45 votes

5 stars: 69 votes

Frequently Asked Questions

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