Create ML for iOS Developers - A Beginner's Guide

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Mohammad Azam

4:11:35

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1. Introduction

1. Introduction.mp4

02:22

2. Prerequisites.mp4

01:23

3. Exercise Files.mp4

00:15

4. What is Machine Learning.mp4

09:10

5. What is Create ML.mp4

01:06

2. Image Detection - Integrating an Existing Model

1. Downloading CoreML Model.mp4

03:16

2. Testing the Model.mp4

09:16

3.1 hello-ml-user-interface.zip

3. Implementing the User Interface.mp4

05:57

4.1 hello-ml-predicting-images.zip

4. Predicting the Image.mp4

12:16

5.1 hello-ml-displaying-predictions.zip

5. Displaying Probabilities.mp4

11:15

6. Resources.html

3. Image Recognition Project - Cats vs Dogs

1. What are you building.mp4

00:29

2. Downloading Image Dataset from Kaggle.mp4

04:27

3. Training and Evaluating Model.mp4

05:40

4.1 HelloCoreML-dogs-vs-cats.zip

4. Integrating Model in an iOS Application.mp4

07:23

5.1 HelloCoreML-cats-and-dogs-int-photo-library.zip

5. Selecting Photo from Photo Library.mp4

15:19

6.1 HelloCoreML-camera.zip

6. Taking Photo from the Camera.mp4

11:55

7. Resources.html

4. Sentiment Analysis Project - News

1. What is Sentiment Analysis.mp4

01:56

2.1 Sentiment Analysis for Financial News.html

2. Downloading the Dataset from Kaggle.mp4

05:48

3.1 sentiment-analysis-swift-playgrounds.zip

3. Training and Creating Model Using Xcode Playgrounds.mp4

16:06

4.1 financial-news-sentimental.zip

4. [Optional] - Extracting Data into Folders Using Python.mp4

10:49

5. [Optional] - Training Using Create ML.mp4

04:51

6.1 FinancialNews-sentiment-app.zip

6. Integrating Model into a SwiftUI Application.mp4

05:34

7. Resources.html

5. Object Detection - Integrating an Existing Model

1. What is Object Detection.mp4

00:58

2. Downloading Object Detection Model from Apple Website.mp4

01:42

3.1 ObjectDetectionDemo-starter.zip

3. Tour of the Starter Project.mp4

01:36

4. Understanding Vision Framework.mp4

01:37

5.1 object-detection-predicting-objects.zip

5. Performing Object Detection Using YOLOv3Tiny Model Through Vision Framework.mp4

13:21

6.1 object-detection-displaying-observations.zip

6. Displaying Observations on the Screen.mp4

05:16

7.1 object-detection-overlay.zip

7. Displaying the Bounding Boxes.mp4

05:20

6. Object Detection - Custom Models

1. What we will be building.mp4

00:33

2.1 Visio ML.html

2. Using Visio ML to Annotate Images.mp4

10:40

3. Training the Object Detection Model.mp4

03:35

4.1 traffic-light-detector-final.zip

4. Integrating TrafficLightObjectDetector.mp4

02:15

5. Resources.html

7. Tabular Data Project Predicting Car Prices Using Carvana Data

1. What we will be building.mp4

01:15

2. Downloading Carvana Dataset from Kaggle.mp4

03:28

3. APIs to Handle Tabular Data.mp4

04:56

4.1 carvana-no-filters.zip

4. Creating ML Model Using DataFrame.mp4

16:28

5.1 honda-toyota.zip

5. Creating ML Model with Specific Criteria.mp4

13:23

6.1 car-names.zip

6. Exporting List of Cars as JSON.mp4

08:53

7.1 final-code.zip

7. Displaying Predicted Car Prices.mp4

08:10

8. Resources.html

8. Conclusion

1. Next Steps.mp4

01:36

2. Bonus Lecture.html

Description

Covers: Image Classification, Object Detection, Sentiment Analysis, Tabular Data, Xcode Playgrounds Training

What You'll Learn?

The fundamentals of Create ML and how to set up their development environment for iOS machine learning projects.
Techniques for image detection, including training models to identify objects and classify images.
The process of sentiment analysis and how to build models that can determine sentiment polarity and perform text classification tasks.
The principles of object detection and how to train models to identify and locate multiple objects within images.
How to work with tabular data and build predictive models using Create ML, enabling accurate predictions and classifications based on structured data.

Who is this for?

iOS developers who want to enhance their app development skills by incorporating machine learning capabilities into their iOS applications.

Swift developers who are interested in exploring the field of machine learning and want to apply it in the context of iOS development.

Students or professionals with a background in iOS development who are looking to expand their skill set and incorporate machine learning into their projects.

Individuals who have a basic understanding of machine learning concepts and want to specifically learn how to utilize the Create ML framework for iOS app development.

Intermediate iOS developers who want to deepen their knowledge of machine learning and gain hands-on experience with creating and integrating machine learning models in their iOS applications.

Those who want to stay up-to-date with the latest advancements in iOS development and machine learning by leveraging Apple's Create ML framework.

What You Need to Know?

Basic knowledge of iOS app development using Swift.

Familiarity with Xcode, Apple's integrated development environment (IDE) for iOS app development.

Access to the latest version of Xcode and the Create ML framework.

A strong understanding of programming concepts, including variables, functions, and control flow.

A desire to learn and apply machine learning techniques to iOS app development.

More details

Description
Are you an iOS developer looking to harness the power of machine learning in your app development projects? Look no further! This comprehensive course, "Create ML for iOS Developers - A Beginner's Guide" is designed to equip you with the knowledge and skills necessary to integrate cutting-edge machine learning models into your iOS applications using Create ML.
In this hands-on course, you will embark on a journey from beginner to proficient iOS machine learning developer. We will start by introducing you to the fundamentals of Create ML, Apple's framework for training machine learning models on-device. You will learn how to set up your development environment, understand the key concepts of machine learning, and get familiar with the Create ML workflow.
As we dive deeper, you will explore the exciting world of image detection. You'll discover how to train models that can identify objects and even classify images with remarkable accuracy. Through practical exercises and real-world examples, you'll learn how to preprocess images, train models using Create ML's intuitive interface, and seamlessly integrate them into your iOS applications.
Next, we'll turn our attention to sentiment analysis, a powerful technique for understanding and classifying text data. You'll learn how to train models that can determine sentiment polarity, analyze customer reviews, and perform text classification tasks. Armed with this knowledge, you'll be able to build engaging and intelligent iOS apps that can interpret and respond to textual data.
But that's not all! We'll also delve into the fascinating field of object detection, where you'll discover how to train models that can identify and locate multiple objects within images. You'll understand the underlying concepts, explore different architectures, and learn how to optimize your models for real-time performance on iOS devices.
Lastly, we'll explore the world of tabular data and learn how to leverage Create ML to build predictive models. You'll understand how to preprocess tabular data, handle missing values, and train models that can make accurate predictions and classifications based on structured data.
By the end of this course, you will have gained the skills and confidence to implement image detection, sentiment analysis, object detection, and tabular data analysis using Create ML in your iOS projects. Whether you're a beginner or an experienced iOS developer, this course will provide you with a solid foundation in machine learning and enable you to create powerful and intelligent applications that will delight your users.
Enroll now and unlock the potential of Create ML in your iOS development journey!
Who this course is for:
iOS developers who want to enhance their app development skills by incorporating machine learning capabilities into their iOS applications.
Swift developers who are interested in exploring the field of machine learning and want to apply it in the context of iOS development.
Students or professionals with a background in iOS development who are looking to expand their skill set and incorporate machine learning into their projects.
Individuals who have a basic understanding of machine learning concepts and want to specifically learn how to utilize the Create ML framework for iOS app development.
Intermediate iOS developers who want to deepen their knowledge of machine learning and gain hands-on experience with creating and integrating machine learning models in their iOS applications.
Those who want to stay up-to-date with the latest advancements in iOS development and machine learning by leveraging Apple's Create ML framework.

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My name is Mohammad Azam and I have been programming in iOS for the last 10+ years. Currently, I am teaching Full Stack Development at DigitalCrafts. Before joining DigitalCrafts I worked as a lead mobile developer for many large companies including Schlumberger, Baker Hughes, AIG and Valic. Currently, I am a senior developer at Blinds Dot Com, a Home Depot company. Before iPhone development I was leading projects in Microsoft ASP technology. I was also awarded the Microsoft MVP award five years in a row due to my contributions in the community.I have also published several of my personal apps to the App Store including Vegetable Tree which was featured by Apple as the most beautiful gardening app on the App Store. I am a frequent speaker at local and national conferences and have authored many articles for many different development magazines.

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