Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs
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Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs

Become a Wizard of all the latest Computer Vision tools that exist out there. Detect anything and create powerful apps.
Bestseller
4.4 (4,927 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
35,356 students enrolled
Last updated 8/2020
English
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Current price: $139.99 Original price: $199.99 Discount: 30% off
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This course includes
  • 11 hours on-demand video
  • 13 articles
  • 6 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • 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
Course content
Expand all 85 lectures 11:05:49
+ Introduction
7 lectures 06:10
BONUS: Learning Paths
00:33
Some Additional Resources!!
00:14

FAQ, Q&A and Bug Help!

This PDF resource will help you a lot!
00:32
FAQBot!
01:29
Get the materials
00:06
Your Shortcut To Becoming A Better Data Scientist!
02:05
+ Module 1 - Face Detection Intuition
8 lectures 01:10:44
Plan of attack
01:27
Updates on Udemy Reviews
01:09
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
9 lectures 57:37
Welcome to the Practical Applications
05:12
Installations Instructions (once and for all!)
14:40

Please see the following debug tips if you are running into any trouble installing PyTorch or to see other common bugs that might pop up. 

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 19:50
Homework Challenge - Instructions
00:39
Homework Challenge - Solution (Video)
19:07
Homework Challenge - Solution (Code files)
00:04
+ Module 2 - Object Detection Intuition
5 lectures 44:14
How SSD is different
09:14
The Multi-Box Concept
10:18
Predicting Object Positions
09:52
Object Detection Intuition
5 questions
+ Module 2 - Object Detection with SSD
11 lectures 01:34:22
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 15:20
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
6 lectures 44:19
Plan of Attack
02:55
The Idea Behind GANs
06:57
How Do GANs Work? (Step 1)
12:12
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
14 lectures 02:01:44
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 bonus video
02:40
+ Annex 1: Artificial Neural Networks
9 lectures 01:30:11
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
Requirements
  • Only High School Maths
  • Basic Python programming knowledge
Description

*** AS SEEN ON KICKSTARTER ***

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 brand 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

Who this course is for:
  • Anyone interested in Computer Vision or Artificial Intelligence