Create Ml For Ios Developers - A Beginner'S Guide

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.

Requirements

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.

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!

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Prerequisites

Lecture 3 Exercise Files

Lecture 4 What is Machine Learning?

Lecture 5 What is Create ML?

Section 2: Image Detection - Integrating an Existing Model

Lecture 6 Downloading CoreML Model

Lecture 7 Testing the Model

Lecture 8 Implementing the User Interface

Lecture 9 Predicting the Image

Lecture 10 Displaying Probabilities

Lecture 11 Resources

Section 3: Image Recognition Project - Cats vs Dogs

Lecture 12 What are you building?

Lecture 13 Downloading Image Dataset from Kaggle

Lecture 14 Training and Evaluating Model

Lecture 15 Integrating Model in an iOS Application

Lecture 16 Selecting Photo from Photo Library

Lecture 17 Taking Photo from the Camera

Lecture 18 Resources

Section 4: Sentiment Analysis Project - News

Lecture 19 What is Sentiment Analysis?

Lecture 20 Downloading the Dataset from Kaggle

Lecture 21 Training and Creating Model Using Xcode Playgrounds

Lecture 22 [Optional] - Extracting Data into Folders Using Python

Lecture 23 [Optional] - Training Using Create ML

Lecture 24 Integrating Model into a SwiftUI Application

Lecture 25 Resources

Section 5: Object Detection - Integrating an Existing Model

Lecture 26 What is Object Detection?

Lecture 27 Downloading Object Detection Model from Apple Website

Lecture 28 Tour of the Starter Project

Lecture 29 Understanding Vision Framework

Lecture 30 Performing Object Detection Using YOLOv3Tiny Model Through Vision Framework

Lecture 31 Displaying Observations on the Screen

Lecture 32 Displaying the Bounding Boxes

Section 6: Object Detection - Custom Models

Lecture 33 What we will be building?

Lecture 34 Using Visio ML to Annotate Images

Lecture 35 Training the Object Detection Model

Lecture 36 Integrating TrafficLightObjectDetector

Lecture 37 Resources

Section 7: Tabular Data Project: Predicting Car Prices Using Carvana Data

Lecture 38 What we will be building?

Lecture 39 Downloading Carvana Dataset from Kaggle

Lecture 40 APIs to Handle Tabular Data

Lecture 41 Creating ML Model Using DataFrame

Lecture 42 Creating ML Model with Specific Criteria

Lecture 43 Exporting List of Cars as JSON

Lecture 44 Displaying Predicted Car Prices

Lecture 45 Resources

Section 8: Conclusion

Lecture 46 Next Steps

Lecture 47 Bonus Lecture

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.