English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 8 Hours | 4.95 GB
Build 7 Cutting-Edge Deep Learning Mobile Applications with React-Native & Python!
Join the most comprehensive React-Native & 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 7 Deep Learning apps that will demonstrate the tools and skills used in order to build scalable, State-of-the-Art Deep Learning React-Native 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 React-Native 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 React-Native 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 React-Native project
- Building a neural network in Keras/Python on Google Collab and exporting it into React-Native project
- Using API’s to perform some Natural Language Processing and implementing those algorithms into our app.
- Use Generative Adversarial Neural Networks to Generate Art!
- And much more!
What you’ll learn
- Learn how to build State-of-the-Art algorithms in Python and then implement them into a React-Native application!
- Build any Neural Networks in Python and then export them into your React-Native application.
- 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.
- Implementing NLP Algorithms in React-Native
- React-Native Machine Learning
- React-Native Deep Learning
Table of Contents
Introduction to Course
1 Introduction to Course
Installing React & VS Code Extensions
2 Getting development environment ready
3 VS Code Extensions used in Course
Learn React-Native
4 Introduction & Setting up the Project
5 Importing UI Dependencies
6 Creating Class
7 Building the UI – Part 1
8 Building the UI – Part 2
9 Styling Output
10 Creating State Variables
11 Increment Count
12 Adding State to UI
Not Hotdog App
13 Introduction & Setting up the Project
14 Importing UI Dependencies
15 Creating Class
16 Building the UI – Part 1
17 Building the UI – Part 2
18 Configuring Image-Picker
19 Functions for Image-Picker
20 Configuring TFlite
21 Functions for TFlite
22 Building our Neural Network in Teachable Machine
23 Integrating Neural Network in our App
24 Storing our Prediction
25 Adding Logic to UI
26 Taking Photo from Device Functionality
PoseNet, MobileNet, SSD, Segmentation & YOLO Neural Networks App
27 Introduction & Setting up the Project
28 Importing UI Dependencies
29 Building the UI
30 Allowing the User to Select Multiple Models
31 Configuring TFlite
32 Functions for TFlite
33 Adding Logic to UI
34 Configuring Image-Picker
35 Functions and UI for Image-Picker
36 Functions for TFlite Predictions
37 Functions to go Back
38 Setting up Functions for Predictions
39 Outputting Prediction Functions – SSD & YOLO
40 Outputting Prediction Functions – Segmentation
41 Outputting Prediction Functions – Pose Net – Part 1
42 Outputting Prediction Functions – Pose Net – Part 2
Flower Classifier App
43 Introduction & Setting up the Project
44 Importing UI Dependencies
45 Creating Class
46 Building the UI – Part 1
47 Building the UI – Part 2
48 Configuring Image-Picker
49 Functions for Image-Picker
50 Configuring TFlite
51 Functions for TFlite
52 Building Neural Network in Python – Getting Data
53 Building Neural Network in Python – Labels & Transfer Learning
54 Building Neural Network in Python – Fitting our Model
55 Using our Model in React-Native
56 Updating UI with Prediction
57 Taking Photo from Device Functionality
Gemstone Classifier
58 Introduction & Setting up the Project
59 Importing UI Dependencies
60 Building the UI – Part 1
61 Building the UI – Part 2
62 Building the UI – Part 3
63 Configuring Image-Picker
64 Functions for Image-Picker
65 Creating State Variables
66 Configuring TFlite
67 Building our Neural Network – Part 1
68 Building our Neural Network – Part 2
69 Building our Neural Network – Part 3
70 Importing Neural to React-Native
71 Making Predictions on User’s Image – Part 1
72 Making Predictions on User’s Image – Part 1
Sentiment Analysis App
73 Introduction & Setting up the Project
74 Importing UI Dependencies
75 Building the UI – Part 1
76 Building the UI – Part 2
77 Finding API
78 Using API in React-Native
79 Outputting Prediction
Black & White Image Colorizer
80 Introduction & Setting up the Project
81 Building the UI – Part 1
82 Building the UI – Part 2
83 Building the UI – Part 3
84 Configuring Image-Picker
85 Functions for Image-Picker
86 Creating State Variables
87 Setting State Variables
88 API
89 Showing Output
90 Fixing Bug
91 Final Touches
Style Transfer App
92 Introduction & Setting up the Project
93 Importing UI Dependencies
94 Building the UI – Part 1
95 Building the UI – Part 2
96 Configuring Image-Picker
97 Functions for Image-Picker
98 Output Page Component
99 Go Back Functionality
100 Integrating API in our App
101 Outputting Prediction Functions – Part 1
102 Final Touches
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