Mô tả

You've definitely heard of AI and Deep Learning. But when you ask yourself, what is my position with respect to this new industrial revolution, that might lead you to another fundamental question: am I a consumer or a creator? For most people nowadays, the answer would be, a consumer.

But what if you could also become a creator?

What if there was a way for you to easily break into the World of Artificial Intelligence and build amazing applications which leverage the latest technology to make the World a better place?

Sounds too good to be true, doesn't it?

But there actually is a way..

Computer Vision is by far the easiest way of becoming a creator.

And it's not only the easiest way, it's also the branch of AI where there is the most to create.

Why? You'll ask.

That's because Computer Vision is applied everywhere. From health to retail to entertainment - the list goes on. Computer Vision is already a $18 Billion market and is growing exponentially.

Just think of tumor detection in patient MRI brain scans. How many more lives are saved every day simply because a computer can analyze 10,000x more images than a human?

And what if you find an industry where Computer Vision is not yet applied? Then all the better! That means there's a business opportunity which you can take advantage of.

So now that raises the question: how do you break into the World of Computer Vision?

Up until now, computer vision has for the most part been a maze. A growing maze.

As the number of codes, libraries and tools in CV grows, it becomes harder and harder to not get lost.

On top of that, not only do you need to know how to use it - you also need to know how it works to maximise the advantage of using Computer Vision.

To this problem we want to bring... 

Computer Vision A-Z.

With this new course you will not only learn how the most popular computer vision methods work, but you will also learn to apply them in practice!

Can't wait to see you inside the class,

Kirill & Hadelin

Bạn sẽ học được gì

Have a toolbox of the most powerful Computer Vision models

Understand the theory behind Computer Vision

Master OpenCV

Master Object Detection

Master Facial Recognition

Create powerful Computer Vision applications

Yêu cầu

  • Only High School Maths
  • Basic Python programming knowledge

Nội dung khoá học

12 sections

Introduction

7 lectures
Welcome Challenge!
02:02
Welcome to the Course!
01:10
Learning Paths
00:33
Some Additional Resources!!
00:14
This PDF resource will help you a lot!
00:32
Get the materials
00:06
Your Shortcut To Becoming A Better Data Scientist!
02:05

Module 1 - Face Detection Intuition

8 lectures
Plan of attack
01:27
Viola-Jones Algorithm
09:35
Haar-like Features
14:42
Integral Image
10:23
Training Classifiers
10:49
Adaptive Boosting (Adaboost)
16:26
Cascading
06:13
Face Detection Intuition
5 questions

Module 1 - Face Detection with OpenCV

10 lectures
Welcome to the Practical Applications
05:12
Installations Instructions (once and for all!)
14:40
Common Debug Tips
00:13
Face Detection - Step 1
06:49
Face Detection - Step 2
05:28
Face Detection - Step 3
03:53
Face Detection - Step 4
05:13
Face Detection - Step 5
04:53
Face Detection - Step 6
11:16
Face Detection with OpenCV
5 questions

Homework Challenge - Build a Happiness Detector

3 lectures
Homework Challenge - Instructions
00:39
Homework Challenge - Solution (Video)
19:07
Homework Challenge - Solution (Code files)
00:04

Module 2 - Object Detection Intuition

6 lectures
Plan of attack
02:08
How SSD is different
09:14
The Multi-Box Concept
10:18
Predicting Object Positions
09:52
The Scale Problem
12:42
Object Detection Intuition
5 questions

Module 2 - Object Detection with SSD

12 lectures
Object Detection - Step 1
09:11
Object Detection - Step 2
05:11
Object Detection - Step 3
07:24
Object Detection - Step 4
08:59
Object Detection - Step 5
05:12
Object Detection - Step 6
17:49
Object Detection - Step 7
05:40
Object Detection - Step 8
03:49
Object Detection - Step 9
14:08
Object Detection - Step 10
16:43
Training the SSD
00:16
Object Detection with SSD
5 questions

Homework Challenge - Detect Epic Horses galloping in Monument Valley

3 lectures
Homework Challenge - Instructions
00:15
Homework Challenge - Solution (Video)
15:01
Homework Challenge - Solution (Code files)
00:04

Module 3 - Generative Adversarial Networks (GANs) Intuition

7 lectures
Plan of Attack
02:55
The Idea Behind GANs
06:57
How Do GANs Work? (Step 1)
12:12
How Do GANs Work? (Step 2)
05:01
How Do GANs Work? (Step 3)
04:23
Applications of GANs
12:51
Generative Adversarial Networks (GANs) Intuition
5 questions

Module 3 - Image Creation with GANs

15 lectures
GANs - Step 1
09:35
GANs - Step 2
18:51
GANs - Step 3
04:54
GANs - Step 4
03:57
GANs - Step 5
19:17
GANs - Step 6
05:30
GANs - Step 7
02:34
GANs - Step 8
09:06
GANs - Step 9
20:28
GANs - Step 10
02:19
GANs - Step 11
06:15
GANs - Step 12
13:51
Image Creation with GANs
5 questions
Special Thanks to Alexis Jacq
02:27
THANK YOU Video
02:40

Annex 1: Artificial Neural Networks

9 lectures
What is Deep Learning?
12:34
Plan of Attack
02:51
The Neuron
16:15
The Activation Function
08:29
How do Neural Networks work?
12:47
How do Neural Networks learn?
12:58
Gradient Descent
10:12
Stochastic Gradient Descent
08:44
Backpropagation
05:21

Annex 2: Convolutional Neural Networks

9 lectures
Plan of Attack
03:31
What are convolutional neural networks?
15:49
Step 1 - Convolution Operation
16:38
Step 1(b) - ReLU Layer
06:41
Step 2 - Pooling
14:13
Step 3 - Flattening
01:52
Step 4 - Full Connection
19:24
Summary
04:19
Softmax & Cross-Entropy
18:20

Congratulations!! Don't forget your Prize :)

2 lectures
Huge Congrats for completing the challenge!
01:28
Bonus: How To UNLOCK Top Salaries (Live Training)
00:44

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