Learn how to build pose detection deep learning iPhone app

Learn how to build pose detection deep learning iPhone app, available at $39.99, has an average rating of 4.4, with 36 lectures, based on 5 reviews, and has 77 subscribers.

You will learn about Use apples coreml and vision api to detect pose in images and videos on mobile devices This course is ideal for individuals who are Intermediate mobile developers who would like to get into deep learning and computer vision area It is particularly useful for Intermediate mobile developers who would like to get into deep learning and computer vision area.

Enroll now: Learn how to build pose detection deep learning iPhone app

Summary

Title: Learn how to build pose detection deep learning iPhone app

Price: $39.99

Average Rating: 4.4

Number of Lectures: 36

Number of Published Lectures: 36

Number of Curriculum Items: 36

Number of Published Curriculum Objects: 36

Original Price: $22.99

Quality Status: approved

Status: Live

What You Will Learn

Use apples coreml and vision api to detect pose in images and videos on mobile devices

Who Should Attend

Intermediate mobile developers who would like to get into deep learning and computer vision area

Target Audiences

Intermediate mobile developers who would like to get into deep learning and computer vision area

Course Description

Learn to build real time pose detection iPhone app using Posenet deep learning algorithm.  Deep learning is popular where a machine can be trained to detect poses in video and images.  Once trained, it can be used to detect poses in any video or image. The app does not require any wifi or cellular connectivity.  It uses deep learning and pretrained posenet model. It leverages apple’s coreml and vision SDK to achieve pose detection entirely on the phone. Since the app does not send your images or vides to remote service, it maintains your privacy and data secured.

Build a strong foundation in pose detection engines  with this tutorial for beginners.

Understanding fundamentals of pose detection

Understanding fundamentals of deep learning and CNN 

Benefits of posenet for fitness apps

Build a real life pose detection in video using posenet, computer vision, coreml and swift

Build a real life pose detection in image  using posenet, computer vision,, coreml and swift

A Powerful Skill at Your Fingertips  Learning the fundamentals of real time pose detection  puts a powerful and very useful tool at your fingertips. swift, posenet and coreml are free, easy to learn, has excellent documentation.

No prior knowledge of CNN or deep learning is assumed. I’ll be covering topics like CNN from scratch.

Jobs in computer vision area are plentiful, and being able to learn real time object detection will give you a strong edge. YOLO is  state of art technology that can quickly help you achieve your goal.

Learning pose detection with posenet will help you become a computer vision developer which is in high demand.

Content and Overview  

This course teaches you on how to build real time pose detection engine using open source posenet, coreml and swift .  You will work along with me step by step to build following answers

Real time pose detection in Video

Real time pose detection in image

Fundamentals of CNN and posenet

What am I going to get from this course?

Learn posenent and build real time pose detection engine from professional trainer from your own desk.

Over 15 lectures teaching you how to build real time pose detection engine

Suitable for intermediate programmers and ideal for users who learn faster when shown.

Visual training method, offering users increased retention and accelerated learning.

Breaks even the most complex applications down into simplistic steps.

Offers challenges to students to enable reinforcement of concepts. Also solutions are described to validate the challenges.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: About Author

Chapter 2: Fundamentals of deep learning

Lecture 1: What is deep learning?

Lecture 2: Difference between Machine Learning, Deep Learning and Artificial Intelligence

Lecture 3: Why deep learning is taking off?

Chapter 3: Internals of deep learning

Lecture 1: Linear Regression

Lecture 2: Logistic regression

Lecture 3: Cost Function

Lecture 4: Gradient Descent

Chapter 4: Deep Learning networks

Lecture 1: Multi Layer Perceptron

Lecture 2: CNN

Lecture 3: Posenet

Chapter 5: Developing Livecapture

Lecture 1: Application Overview

Lecture 2: Setting up Video Capture Part I

Lecture 3: Setting up Video Capture Part II

Lecture 4: Setting up Video Capture Part III

Chapter 6: Developing Posenet model , input and output

Lecture 1: Using Posenet model to detect poses part I

Lecture 2: Developing Posenet output part I

Lecture 3: Developing Posenet outoput part II

Lecture 4: Developing posenet output part III

Lecture 5: Developing Posenet output part IV

Lecture 6: Developing Posenet model inference

Chapter 7: Developing Posenet Builder

Lecture 1: Pose Configuaration and Pose Structure

Lecture 2: Pose Builder

Lecture 3: Single Pose Builder

Lecture 4: Multiple Pose Builder Part I

Lecture 5: Multiple Pose Builder Part II

Lecture 6: Multiple Pose Builder Part III

Chapter 8: Developing viewcontroller

Lecture 1: Configuration View Controller Part I

Lecture 2: Configuration View Controller Part II

Lecture 3: PopOver Presentation View Controller

Lecture 4: Pose Image View

Lecture 5: Pose Image View Part II

Lecture 6: Main View Controller

Chapter 9: Running Posenet App

Lecture 1: Pose detection

Lecture 2: Next Steps

Instructors

Evergreen Technologies
Software Mentor

Rating Distribution

1 stars: 0 votes

2 stars: 1 votes

3 stars: 0 votes

4 stars: 1 votes

5 stars: 3 votes

Frequently Asked Questions

How long do I have access to the course materials?

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

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!