Building iOS Question Answering App with BERT

Building iOS Question Answering App with BERT, available at $54.99, has an average rating of 4.56, with 24 lectures, based on 8 reviews, and has 69 subscribers.

You will learn about Learn to develop machine learning based question answering iOS application Learn to convert speech into text Learn to convert text into speech Learn state of the art Natural Language Processing language modeling technology called BERT This course is ideal for individuals who are Beginner iOS developers who would like to build mobile apps using deep learning It is particularly useful for Beginner iOS developers who would like to build mobile apps using deep learning.

Enroll now: Building iOS Question Answering App with BERT

Summary

Title: Building iOS Question Answering App with BERT

Price: $54.99

Average Rating: 4.56

Number of Lectures: 24

Number of Published Lectures: 24

Number of Curriculum Items: 24

Number of Published Curriculum Objects: 24

Original Price: $22.99

Quality Status: approved

Status: Live

What You Will Learn

Learn to develop machine learning based question answering iOS application

Learn to convert speech into text

Learn to convert text into speech

Learn state of the art Natural Language Processing language modeling technology called BERT

Who Should Attend

Beginner iOS developers who would like to build mobile apps using deep learning

Target Audiences

Beginner iOS developers who would like to build mobile apps using deep learning

This course teaches you step by step on how tp build iOS question answering application. It explores the world of machine learning from application developer’s perspective. It explains the world of word embeddings which is fundamental technology behind text processing. As Andrew Ng has said “AI is new electricity”. The course highlight difference among AI (Artificial Intelligence, Machine learning and deep learning.  It also teaches few embedding technologies like glove, word2vec and BERT.

BERT is state of art transformer model developed by Google and has proven to be equivalent of CNN in computer vision technology. This course uses pretrained BERT model and explains how to use it in IOS question answering app.

The students once armed with this knowledge will be able to demonstrate their command  on machine learning and can use this technology for several different apps.

The author assumes that the student does not have any background in machine learning.

The course is structured as follows

App Preview : Shows preview of app that we are going to build

Embeddings : Explains what word embeddings are and why are they important

Deep Neural Network : It covers fundamentals of deep learning, and multi layer perceptron

BERT, Glove, Word2Vec : Popular word embedding technologies

Build UI from scratch :  Shows how to build UI by using basic controls in iOS swift

Step by Step Coding : Each function is explained in details with step by step walkthrough of the code

Text to Speech and Speech to text : This sections explains how to use test to speech and speech top text conversion libraries in iOS app so that user can speak question into the app and hear the answer . This is extremely useful for physically challenged users who can not type using keyboard

Run the app on iPhone : Shows the flow of the app on the phone.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: About Author

Lecture 3: Preview of app that we are going to build

Chapter 2: World of word embeddings

Lecture 1: What are word embeddings?

Lecture 2: One hot encodings

Lecture 3: Deep neural network

Lecture 4: Word2vec

Lecture 5: Glove embeddings

Lecture 6: BERT

Chapter 3: Mobile App

Lecture 1: Source Code

Lecture 2: Creating Single View App

Chapter 4: BERT Module

Lecture 1: BERT model

Lecture 2: BERT Vocabulary

Lecture 3: Tokenizer Part I

Lecture 4: Tokenizer Part II

Lecture 5: BERT Input

Lecture 6: BERT output

Lecture 7: BERT Facade

Chapter 5: Speech

Lecture 1: Converting speech to text

Lecture 2: Converting text to speech

Chapter 6: Bringing it all together

Lecture 1: Finding answer to question

Lecture 2: Building App

Lecture 3: Running app

Lecture 4: 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: 6 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!