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IOS & ML 2024 – Train Tensorflow Lite Models for IOS Apps

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IOS & ML 2024 – Train Tensorflow Lite Models for IOS Apps, available at $54.99, with 73 lectures, and has 14 subscribers.

You will learn about Train Machine Learning Models & deploy them in IOS Swift Applications Use of Tensorflow Lite models in IOS Swift Applications Train a machine learning model and build a House Price Prediction IOS Swift Application Train a machine learning model and build a Fuel Efficiency Prediction IOS Swift Application Lean basic syntax of python programming language to train ML models for IOS Swift Applications Learn basics of Machine Learning & Deep Learning for training Machine learning Models for smart IOS Development Understand the working of artificial neural networks for training machine learning for IOS Swift Apps Learn use of data science libraries like numpy, pandas and matplotlib for training Machine learning models for IOS Swift Apps Learn to analyse & use advance linear regression models for use in IOS Swift Applications Learn Data Collection & Preprocessing for Machine Learning model training for IOS Swift Applications Learn to train Countless Prediction models for IOS Swift Applications This course is ideal for individuals who are Beginner IOS Developer who want to build Machine Learning based IOS Applications or Intermediate IOS developers eager to add Machine Learning to their skillset or IOS experts seeking to bridge the gap between Machine Learning and Mobile App Development or Anyone who want to train custom machine learning models and build IOS Swift Applications It is particularly useful for Beginner IOS Developer who want to build Machine Learning based IOS Applications or Intermediate IOS developers eager to add Machine Learning to their skillset or IOS experts seeking to bridge the gap between Machine Learning and Mobile App Development or Anyone who want to train custom machine learning models and build IOS Swift Applications.

Enroll now: IOS & ML 2024 – Train Tensorflow Lite Models for IOS Apps

Summary

Title: IOS & ML 2024 – Train Tensorflow Lite Models for IOS Apps

Price: $54.99

Number of Lectures: 73

Number of Published Lectures: 73

Number of Curriculum Items: 73

Number of Published Curriculum Objects: 73

Original Price: $109.99

Quality Status: approved

Status: Live

What You Will Learn

  • Train Machine Learning Models & deploy them in IOS Swift Applications
  • Use of Tensorflow Lite models in IOS Swift Applications
  • Train a machine learning model and build a House Price Prediction IOS Swift Application
  • Train a machine learning model and build a Fuel Efficiency Prediction IOS Swift Application
  • Lean basic syntax of python programming language to train ML models for IOS Swift Applications
  • Learn basics of Machine Learning & Deep Learning for training Machine learning Models for smart IOS Development
  • Understand the working of artificial neural networks for training machine learning for IOS Swift Apps
  • Learn use of data science libraries like numpy, pandas and matplotlib for training Machine learning models for IOS Swift Apps
  • Learn to analyse & use advance linear regression models for use in IOS Swift Applications
  • Learn Data Collection & Preprocessing for Machine Learning model training for IOS Swift Applications
  • Learn to train Countless Prediction models for IOS Swift Applications

Who Should Attend

  • 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
  • Anyone who want to train custom machine learning models and build IOS Swift Applications

Target Audiences

  • 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
  • Anyone who want to train custom machine learning models and build IOS Swift Applications

Do you want to train different Machine Learning models and build smart iOS Swift applications? Then welcome to this comprehensive course!

My name is Muhammad Hamza Asif, and I am the leading Mobile Machine Learning instructor on Udemy. In this course, we’ll embark on a journey to combine the power of predictive modeling with the flexibility of iOS app development using Swift and SwiftUI. Whether you’re a seasoned iOS developer or new to the scene, this course has something valuable to offer you.

Course Highlights:

Training Your First Machine Learning Model:

  • Use TensorFlow and Python to create a simple Machine Learning (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 Swift:

  • Apply your knowledge to a real-world problem by predicting automobile fuel efficiency.

  • Seamlessly integrate the model into an iOS Swift app for an intuitive fuel efficiency prediction experience.

House Price Prediction in iOS Swift:

  • Master the art of training regression models on substantial datasets.

  • Utilize the trained model within your iOS Swift app to predict house prices confidently.

Regression is one of the fundamental techniques in Machine Learning which can be used for countless applications. Inside this course, you will learn to train your custom machine learning models in TensorFlow Lite and build smart iOS Swift applications.

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

The iOS-ML Fusion: After grasping the core concepts, we’ll bridge the gap between iOS Swift and Machine Learning. 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.

The iOS Development 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 Swift developers eager to add predictive modeling to their skillset.

  • Beginner iOS Swift developers with very little knowledge of mobile app development.

  • Intermediate iOS Swift developers wanting to build powerful Machine Learning-based applications in iOS Swift.

  • Experienced iOS Swift developers wanting to use Machine Learning models inside their iOS applications.

  • Enthusiasts seeking to bridge the gap between Machine Learning and iOS development.

Step into the World of iOS Development and Predictive Modeling: Join us on this exciting journey and unlock the potential of iOS Swift and Machine Learning. By the end of the course, you’ll be ready to develop iOS Swift applications that not only look great but also make informed, data-driven decisions.

Enroll now and embrace the fusion of iOS Swift and Machine Learning!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: IOS Development With Machine Learning Course Curriculum

Chapter 2: Machine Learning & Deep Learning for IOS Swift

Lecture 1: What is Machine Learning – Swift IOS Development

Lecture 2: Supervised Machine Learning – Swift IOS Development

Lecture 3: Regression and Classification – Swift IOS Development

Lecture 4: Unsupervised Machine Learning & Reinforcement Learning – Swift IOS Development

Lecture 5: Deep Learning and Neural Network Introduction – Swift IOS Development

Lecture 6: Neural Network Example – Swift IOS Development

Lecture 7: Basic Deep Learning Concepts – Swift IOS Development

Chapter 3: Python Programming Language for IOS Swift

Lecture 1: Google Colab Introduction – Swift IOS Development

Lecture 2: Python Introduction & data types – Swift IOS Development

Lecture 3: Python Numbers – Swift IOS Development

Lecture 4: Python Strings – Swift IOS Development

Lecture 5: Python Lists – Swift IOS Development

Lecture 6: Python dictionary & tuples – Swift IOS Development

Lecture 7: Python loops & conditional statements – Swift IOS Development

Lecture 8: File handling in Python – Swift IOS Development

Chapter 4: Data Science Libraries for Swift IOS Development

Lecture 1: Numpy Introduction – Swift IOS Development

Lecture 2: Numpy Functions and Generating Random Values – Swift IOS Development

Lecture 3: Numpy Operators – Swift IOS Development

Lecture 4: Matrix Multiplications and Sorting in Numpy – Swift IOS Development

Lecture 5: Pandas Introduction – Swift IOS Development

Lecture 6: Loading CSV in pandas – Swift IOS Development

Lecture 7: Handling Missing values in dataset with pandas – Swift IOS Development

Lecture 8: Matplotlib & charts in python – Swift IOS Development

Lecture 9: Dealing images with Matplotlib – Swift IOS Development

Chapter 5: Tensorflow & Tensorflow Lite for IOS Swift

Lecture 1: Tensorflow Introduction | Variables & Constants – IOS SwiftUI

Lecture 2: Shapes & Ranks of Tensors – IOS SwiftUI

Lecture 3: Matrix Multiplication & Ragged Tensors – IOS SwiftUI

Lecture 4: Tensorflow Operations – IOS SwiftUI

Lecture 5: Generating Random Values in Tensorflow – IOS SwiftUI

Lecture 6: Tensorflow Checkpoints – IOS SwiftUI

Lecture 7: Tensorflow Lite Introduction & Advantages – IOS SwiftUI

Chapter 6: Training a basic Machine Learning ( Linear Regression) model for IOS Swift

Lecture 1: Section Introduction

Lecture 2: Train a simple regression model for Swift IOS Development

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

Lecture 4: Model training for IOS Swift app development overview

Lecture 5: Creating a new IOS SwiftUI project and the GUI of Swift Application

Lecture 6: Adding Tensorflow Lite Models in IOS Swift Application

Lecture 7: Loading Tensorflow Lite Models in IOS Swift Application

Lecture 8: Preparing Input for Tensorflow Lite Models and Passing it in IOS Swift App

Lecture 9: Getting Output from Tensorflow Lite model and showing it on IOS Swift App

Lecture 10: Tensorflow Lite Models Integration in IOS Swift App Overview

Chapter 7: Training a Fuel Efficiency Prediction Model for IOS Swift Application

Lecture 1: Section Introduction

Lecture 2: Getting datasets for training a fuel efficiency prediction model for IOS Apps

Lecture 3: Loading dataset in python with pandas

Lecture 4: Handling Missing Values in Dataset

Lecture 5: One Hot Encoding: Handling categorical columns

Lecture 6: Training and testing datasets

Lecture 7: Normalization Introduction

Lecture 8: Normalization: Bringing all columns to a common scale

Lecture 9: Training a fuel efficiency prediction model for IOS Swift Application

Lecture 10: Testing fuel efficiency prediction model and converting it to a tflite format

Lecture 11: Fuel Efficiency Model Training Overview

Chapter 8: Fuel Efficiency Prediction IOS Swift Application

Lecture 1: Setup Starter Swift IOS Application for Fuel Efficiency Prediction

Lecture 2: GUI of Fuel Efficiency Prediction Swift IOS Application

Lecture 3: Adding Tensorflow Lite Library in IOS Swift Application

Lecture 4: Loading Fuel Efficiency Prediction tflite model in IOS Swift Application

Lecture 5: Preparing Input for Tensorflow Lite Model in Swift IOS Application

Lecture 6: Passing input to tflite model and getting output in IOS Swift Application

Lecture 7: Normalizing Input for Tensorflow Lite Models in IOS Swift Application

Lecture 8: Important things to remember while using Tensorflow Lite Models in IOS Apps

Chapter 9: Training House Price Prediction Model for IOS Swift Applications

Lecture 1: Section Introduction

Lecture 2: Getting house price prediction dataset for model training for IOS Development

Lecture 3: Load dataset for training house price prediction tflite model for Swift IOS Apps

Lecture 4: Training & evaluating house price prediction model for Swift IOS Apps

Lecture 5: Retraining price prediction model

Chapter 10: House Price Prediction IOS Application

Lecture 1: Setting Up House Price Prediction IOS Swift Application

Lecture 2: GUI of House Price Prediction IOS Swift Application With SwiftUI

Lecture 3: Adding Tensorflow Lite Library in IOS Swift Application

Lecture 4: Loading Tensorflow Lite Model in IOS Swift Application

Lecture 5: Passing Input to Tensorflow Lite Model and Get prediction for House Price

Lecture 6: House Price Prediction Application Testing

Instructors

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Frequently Asked Questions


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You can view and review the lecture materials indefinitely, like an on-demand channel.


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