IOS & ML: Train Machine Learning models for IOS SwiftUI Apps

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Hamza Asif

5:19:38

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1. Introduction

1. Introduction.mp4

03:00

2. Machine Learning & Deep Learning for IOS Swift

1. Machine Learning Introduction.mp4

03:25

2. Supervised Machine Learning Regression & Classification.mp4

04:42

3. Unsupervised Machine Learning & Reinforcement Learning.mp4

03:21

4. Deep Learning and regression models training.mp4

13:04

5. Basic Deep Learning Concepts.mp4

06:13

3. Python Programming Language for IOS Swift

1. Google Colab Introduction.mp4

04:58

2.1 Python.zip

2. Python Introduction & data types.mp4

08:34

3. Python Lists.mp4

06:03

4. Python dictionary & tuples.mp4

03:40

5. Python loops & conditional statements.mp4

03:58

6. File handling in Python.mp4

04:21

4. Data Science Libraries for IOS

1.1 DataScience Libraries.zip

1. Numpy Introduction.mp4

05:22

2. Numpy Operations.mp4

04:41

3. Numpy Functions.mp4

04:33

4. Pandas Introduction.mp4

03:29

5. Loading CSV in pandas.mp4

03:13

6. Handling Missing values in dataset with pandas.mp4

03:41

7. Matplotlib & charts in python.mp4

03:21

8. Dealing images with Matplotlib.mp4

02:40

5. Tensorflow & Tensorflow Lite for IOS Swift

1.1 Tensorflow.zip

1. Tensorflow Introduction Variables & Constants.mp4

05:37

2. Shapes & Ranks of Tensors.mp4

05:23

3. Matrix Multiplication & Ragged Tensors.mp4

05:21

4. Tensorflow Operations.mp4

02:06

5. Generating Random Values in Tensorflow.mp4

06:38

6. Tensorflow Checkpoints.mp4

03:29

6. Training a basic regression model for IOS Swift

1. Section Introduction.mp4

02:27

2.1 Basic Example.zip

2. Train a simple regression model for IOS Swift.mp4

09:56

3. Testing model and converting it to a tflite(Tensorflow lite) format for IOS.mp4

03:26

4. Model training for IOS Swift app development overview.mp4

02:00

5. Creating a new IOS SwiftUI project and the GUI of Swift Application.mp4

08:40

6. Adding Tensorflow Lite Models in IOS Swift Application.mp4

05:46

7. Loading Tensorflow Lite Models in IOS Swift Application.mp4

07:30

8. Preparing Input for Tensorflow Lite Models and Passing it in IOS Swift App.mp4

07:07

9. Getting Output from Tensorflow Lite model and showing it on IOS Swift App.mp4

04:25

10. Tensorflow Lite Models Integration in IOS Swift App Overview.mp4

03:07

7. Training a Fuel Efficiency Prediction Model for IOS Swift Application

1. Section Introduction.mp4

02:05

2.1 FuelEfficiencyPrediction.zip

2. Getting datasets for training regression models for IOS.mp4

04:56

3. Loading dataset in python with pandas.mp4

07:45

4. Handling Missing Values in Dataset.mp4

03:24

5. One Hot Encoding Handling categorical columns.mp4

04:38

6. Training and testing datasets.mp4

04:19

7. Normalization Bringing all columns to a common scale.mp4

02:40

8. Training a fuel efficiency prediction model for IOS Swift Application.mp4

07:04

9. Testing fuel efficiency prediction model and converting it to a tflite format.mp4

04:20

10. Fuel Efficiency Model Training Overview.mp4

04:30

8. Fuel Efficiency Prediction IOS Swift Application

1. Setup Starter IOS Application for Fuel Efficiency Prediction.mp4

04:07

2. GUI of Fuel Efficiency Prediction IOS Application.mp4

08:15

3. Adding Tensorflow Lite Library in IOS Swift Application.mp4

03:28

4. Loading Fuel Efficiency Prediction tflite model in IOS Swift Application.mp4

04:46

5. Preparing Input for Tensorflow Lite Model.mp4

08:04

6. Passing input to tflite model and getting output in IOS Swift Application.mp4

06:47

7. Normalizing Input for Tensorflow Lite Models in IOS Swift Application.mp4

09:18

8. Important things to remember while using Tensorflow Lite Models in IOS Apps.mp4

01:56

9. Training House Price Prediction Model for IOS

1. Section Introduction.mp4

02:09

2.1 HousePricePrediction.zip

2. Getting house price prediction dataset.mp4

03:45

3. Load dataset for training house price prediction tflite model for IOS.mp4

07:19

4. Training & evaluating house price prediction model for IOS.mp4

06:30

5. Retraining price prediction model.mp4

04:04

10. House Price Prediction IOS Application

1. Setting Up House Price Prediction IOS Swift Application.mp4

04:10

2. GUI of House Price Prediction IOS Swift Application With SwiftUI.mp4

02:39

3. Adding Tensorflow Lite Library in IOS Swift Application.mp4

03:29

4. Loading Tensorflow Lite Model in IOS Swift Application.mp4

03:49

5. Passing Input to Tensorflow Lite Model and Get prediction for House Price.mp4

07:41

6. House Price Prediction Application Testing.mp4

02:24

Description

Use Tensorflow Lite models in IOS with SwiftUI | Train Machine Learning Models for IOS Swift Applications | SwiftUI

What You'll Learn?

Train Machine Learning models for IOS Swift Applications
Integrate Machine Learning models in IOS with SwiftUI
Use of Tensorflow Lite models in IOS Swift App
Analysing & using advance regression models in IOS Swift Applications
Train a machine learning model and build a house price prediction IOS Application
Train a machine learning model and build a fuel efficiency prediction IOS Swift Application
Train Any Prediction Model & use it in IOS Swift Applications
Data Collection & Preprocessing for ML model training for IOS Swift Application
Basics of Machine Learning & Deep Learning for training Machine learning Models for smart IOS App Development
Understand the working of artificial neural networks for training machine learning for IOS Swift Apps
Basic syntax of python programming language to train ML models for IOS Swift Applications
Use of data science libraries like numpy, pandas and matplotlib

Who is this for?

Beginner IOS Developer who want to build Machine Learning based IOS Applications

Intermediate IOS developers eager to add Machine Learning to their skillset

IOS experts seeking to bridge the gap between Machine Learning and Mobile App Development

What You Need to Know?

XCode Installed on your MAC

More details

Description
Do you want to train different Machine Learning models and build smart IOS applications then Welcome to this course.

Regression is one of the fundamental techniques in Machine Learning which can be used for countless applications. Like you can train Machine Learning models using regression
to predict the price of the house
to predict the Fuel Efficiency of vehicles
to recommend drug doses for medical conditions
to recommend fertilizer in agriculture
to suggest exercises for improvement in player performance
and so on. So Inside this course, you will learn to train your custom machine learning models in Tensorflow lite and build smart IOS Swift applications.

I'm Muhammad Hamza Asif, and in this course, we'll embark on a journey to combine the power of predictive modeling with the flexibility of IOS app development. Whether you're a seasoned IOS developer or new to the scene, this course has something valuable to offer you

Course Overview: We'll begin by exploring the basics of Machine Learning and its various types, and then dive into the world of deep learning and artificial neural networks, which will serve as the foundation for training our Tensorflow LiteÂ models for IOS Applications.

The IOS-ML Fusion: After grasping the core concepts, we'll bridge the gap between IOS and Machine Learning. To do this, we'll kickstart our journey with Python programming, a versatile language that will pave the way for our Machine Learning model training

Unlocking Data's Power: To prepare and analyze our datasets effectively, we'll dive into essential data science libraries like NumPy, Pandas, and Matplotlib. These powerful tools will equip you to harness data's potential for accurate predictions.

Tensorflow for Mobile: Next, we'll immerse ourselves in the world of TensorFlow, a library that not only supports model training using neural networks but also caters to mobile devices.

Course Highlights:
Training Your First Regression Model:
Use TensorFlow and Python to create a simple regression model
Convert the model into TFLite format, making it compatible with IOS Swift
Learn to integrate the TFLite model into IOS Swift apps
Fuel Efficiency Prediction in IOS:
Apply your knowledge to a real-world problem by predicting automobile fuel efficiency
Seamlessly integrate the model into a IOS Swift app for an intuitive fuel efficiency prediction experience
House Price Prediction in IOS:
Master the art of training regression models on substantial datasets
Utilize the trained model within your IOS app to predict house prices confidently

The IOS Advantage: By the end of this course, you'll be equipped to:
Train advanced regression models for accurate predictions
Seamlessly integrate ML models into your IOS Swift applications
Analyze and use existing tflite models effectively within the IOS Swift ecosystem

Who Should Enroll:
Aspiring IOS developers eager to add predictive modeling to their skillset
Beginner IOS Swift developer with very little knowledge of mobile app development
Intermediate IOS Swift developer wanted to build a powerful Machine Learning-based application in IOS Swift
Experienced IOS Swift developers wanted to use Machine Learning models inside their IOS applications.
Enthusiasts seeking to bridge the gap between Machine Learning and IOS app development

Step into the World of IOS and Predictive Modeling: Join us on this exciting journey and unlock the potential of IOS and Machine Learning. By the end of the course, you'll be ready to develop IOS applications that not only look great but also make informed, data-driven decisions.
Enroll now and embrace the fusion of IOS and Machine Learning
Who this course is for:
Beginner IOS Developer who want to build Machine Learning based IOS Applications
Intermediate IOS developers eager to add Machine Learning to their skillset
IOS experts seeking to bridge the gap between Machine Learning and Mobile App Development

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Experienced Mobile Developer, specialized in Mobile Machine Learning using Tensorflow lite, ML Kit, and Google cloud vision API. Leading Android Machine learning instructor with over 50,000 students from 150 countries. I am an enthusiastic developer with a strong programming background and possess great app development skills. I have developed a bunch of native and cross-platform apps in the past and satisfied all of my clients. It has been +4 years doing Mobile development and providing support for Android Applications. Empowering mobile Applications using Machine Learning and Computer vision is my core skill.Powering Android Application with ML really fascinates me. So I learned Android development and then Machine Learning. I developed Android applications for several multinational organizations. Now I want to spread the knowledge I have. I'm always thinking about how to make difficult concepts easy to understand, what kind of projects would make a fun tutorial, and how I can help you succeed through my courses.

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