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2021-03-01 20:16:50
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IT & Software Other IT & Software Deep Learning

Deep Learning Course with Flutter & Python - Build 6 AI Apps

Build 6 Cutting-Edge Deep Learning Mobile Applications with Flutter & Python!
Bestseller
Rating: 4.6 out of 54.6 (175 ratings)
10,825 students
Created by Samuel Boylan-Sajous
Last updated 9/2020
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • Learn how to build State-of-the-Art algorithms in Python and then implement them into a Flutter application!
  • Build any Neural Networks in Python and then export them into your Flutter application.
  • Have a clear understanding of different types of Neural Networks and how you can use them to your advantage.
  • The tools and skills to develop any AI idea you have onto a mobile phone.
  • Use different strategies to get Neural Networks with 90%+ accuracy.
  • Building GAN in Python and Implementing it in Flutter
  • Building CNN in Python and Implementing it in Flutter
  • Implementing NLP Algorithms in Flutter
  • Flutter Machine Learning
Curated for the Udemy for Business collection

Requirements

  • Intermediate Programmer
  • Know some theory behind Neural Networks.
  • Curiosity

Description

Join the most comprehensive Flutter & Deep Learning course on Udemy and learn how to build amazing state-of-the-art Deep Learning applications!

Do you want to learn about State-of-the-art Deep Learning algorithms and how to apply them to IOS/Android apps? Then this course is exactly for you! You will learn how to apply various State-of-the-art Deep Learning algorithms such as GAN's, CNN's, & Natural Language Processing. In this course, we will build 6 Deep Learning apps that will demonstrate the tools and skills used in order to build scalable, State-of-the-Art Deep Learning Flutter applications!

After completing this course you will be able to:

  • Learn the tools and skills to develop any AI idea you have onto a mobile phone.

  • Have a clear understanding of different types of Neural Networks and how you can use them to your advantage.

  • Build any Neural Networks in Python and then export them into your Flutter application.

  • Use different strategies to get neural networks with 90%+ accuracy.

Why should you choose this course?

This course covers all the steps that one should take to create a Flutter application that uses State-of-the-Art Deep Learning approaches.

It is extremely hard to find good tutorials that teach you how to implement these algorithms, so the instructor, Samuel Boylan-Sajous, who has been programming for years, and has a Computer Science degree at the University of Guelph, has decided to share all of his knowledge with other students that are passionate about Deep Learning and building practical A.I. applications.

Here's what's included in the course:

  • Building a neural network on Teachable Machine and exporting it into Flutter project

  • Building a neural network in Keras/Python on Google Collab/Jupyter Notebook and exporting it into Flutter project

  • Using API's to perform some Natural Language Processing and implementing those algorithms into our app.

  • Build a GAN in python and implement it into your flutter application.

  • And much more!

This course is for you if ...

  • You're interested in building real native mobile apps for the two most popular mobile platforms - iOS and Android

  • You're passionate about Deep Learning/AI or Mobile Development and want to expand your knowledge.

  • You want to expand your Deep Learning/AI portfolio with 6 Cutting Edge Deep Learning apps!

  • Want to learn State-of-the-Art Deep Learning algorithms and how you can use them on a mobile device!

Course prerequisites:

  • Knowing mobile development will help a lot but is not a hard requirement (You would be fine if you only knew CSS/HTML & Object-Oriented Programming, just do some research on what Flutter is)

  • Know some theory behind Neural Networks (Know how data is processed in a Neural Network)

Our Promise

Teaching our students is my job and I am committed to it. If you have any questions about the course content or anything related to any topic, you can always post a question in the course or send me a direct message.

Who this course is for:

  • Beginner/Intermediate Flutter developers
  • People that want to learn Deep Learning for mobile development
  • People that want to apply State-of-the-Art Deep Learning Algorithms to mobile apps
  • Want to build State-of-the-Art Deep Learning/A.I. applications

Course content

10 sections • 61 lectures • 6h 45m total length

  • Preview04:00
  • Preview01:31
  • Preview02:47

  • Preview06:31

  • Preview00:32
  • Preview03:12
  • Preview07:43
  • Preview04:22
  • Preview07:48
  • Preview09:51
  • Preview08:19
  • Preview02:17
  • Preview06:10

  • Introduction
    00:55
  • Setting up the Project
    04:51
  • Setting up Home - Part 1
    11:18
  • Setting up Home - Part 2
    02:29
  • Setting up Home - Part 3
    05:21
  • Google Collab Introduction
    02:42
  • Preprocessing our Data
    11:15
  • Building our Neural Network & Exporting it
    15:05
  • Finishing and Testing our app!
    04:25

  • IFruit App Review
    00:50
  • Introduction & Setting up the Project
    01:59
  • Setting up Home
    03:38
  • Getting Dataset & Starting new Notebook
    04:35
  • Building our Neural Network - Part 1
    07:02
  • Building our Neural Network - Part 2
    06:25

  • Sentiment Analysis App Review
    01:18
  • Introduction & Setting up the Project
    06:42
  • Setting up Home - Part 1
    04:25
  • Setting up Home - Part 2
    05:40
  • Setting up Home - Part 3
    04:18
  • Set up functions for API in Flutter App
    11:06
  • Implement API in Flutter App & Finalizing
    09:56

  • Introduction & Setting up the Project
    07:55
  • Setting up Home - Part 1
    06:19
  • Setting up Home - Part 2
    06:30
  • Creating Functions in Home
    05:00
  • Connecting to API Service Red Hat
    05:32
  • Fetching Response
    10:06
  • Adding Logic & Testing API
    08:33
  • Live Camera Functionality - Part 1
    12:37
  • Live Camera Functionality - Part 2 & Finalizing
    15:58

  • Introduction & Setting up the Project
    03:28
  • Setting up Home
    06:13
  • Drawing functionality - Part 1
    09:14
  • Drawing functionality - Part 2
    06:31
  • Saving User Sketch
    16:49
  • Clear Sketch Functionality
    01:38
  • Adding Logic & New Screen
    06:31
  • Building our Neural Network
    11:05
  • Going over Pix2Pix Algorithm & Training
    08:48
  • Reviewing our Neural Network
    04:08
  • Flask Introduction
    06:26
  • Building a Flask Server to Deploy our Neural Network
    16:07
  • Building our API for Flask
    14:50
  • Interacting with Flask & Debugging
    15:02

  • Adding library image as input!
    06:23
  • Finding a larger Edges2Shoes dataset & other Pix2Pix Datasets!
    02:28

  • Code & my LinkedIn!
    00:17

Instructor

Samuel Boylan-Sajous
Developer & Teacher
Samuel Boylan-Sajous
  • 4.6 Instructor Rating
  • 227 Reviews
  • 13,208 Students
  • 4 Courses

Hey! I'm Samuel. I love working with cutting edge technologies and teaching them. I have a degree in Computer Science from the University of Guelph and years of programming experience in multiple languages. Technology is my passion!


I hope you learn a lot and happy coding :)


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