Deep Learning and Computer Vision A-Z: OpenCV, SSD & GANs
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       Video Length : 14h00m0s
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       Tasks Number : 95
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       Students Enrolled : 1023
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       Medium Level
  • Curriculum
  • 1. Introduction
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      Welcome to the Course
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      Some Additional Resources
      10m0s
  • 2. Module 1 - Face Detection Intuition
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      Plan of attack
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      Viola-Jones Algorithm
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      Updates on Udemy Reviews
      10m0s
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      Haar-like Features
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      Integral Image
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      Training Classifiers
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      Adaptive Boosting (Adaboost)
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      Cascading
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      Face Detection Intuition
      10m0s
  • 3. Module 1 - Face Detection with OpenCV
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      Welcome to the Practical Applications
      10m0s
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      Installations Instructions (once and for all!)
      10m0s
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      Common Debug Tips
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      Face Detection - Step 1
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      Face Detection - Step 2
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      Face Detection - Step 3
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      Face Detection - Step 4
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      Face Detection - Step 5
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      Face Detection - Step 6
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      Face Detection with OpenCV
      10m0s
  • 4. Homework Challenge - Build a Happiness Detector
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      Homework Challenge - Instructions
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      Homework Challenge - Solution (Video)
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      Homework Challenge - Solution (Code files)
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  • 5. Module 2 - Object Detection Intuition
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      Plan of attack
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      How SSD is different
      10m0s
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      The Multi-Box Concept
      10m0s
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      Predicting Object Positions
      10m0s
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      The Scale Problem
      10m0s
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      Object Detection Intuition
      10m0s
  • 6. Module 2 - Object Detection with SSD
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      Object Detection - Step 1
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      Object Detection - Step 2
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      Object Detection - Step 3
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      Object Detection - Step 4
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      Object Detection - Step 5
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      Object Detection - Step 6
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      Object Detection - Step 7
      10m0s
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      Object Detection - Step 8
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      Object Detection - Step 9
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      Object Detection - Step 10
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      Training the SSD
      10m0s
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      Object Detection with SSD
      10m0s
  • 7. Homework Challenge - Detect Epic Horses galloping in Monument Valley
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      Homework Challenge - Instructions
      10m0s
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      Homework Challenge - Solution (Video)
      10m0s
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      Homework Challenge - Solution (Code files)
      10m0s
  • 8. Module 3 - Generative Adversarial Networks (GANs) Intuition
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      Plan of Attack
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      The Idea Behind GANs
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      How Do GANs Work? (Step 1)
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      How Do GANs Work? (Step 2)
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      How Do GANs Work? (Step 3)
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      Applications of GANs
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      Generative Adversarial Networks (GANs) Intuition
      10m0s
  • 9. Module 3 - Image Creation with GANs
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      GANs - Step 1
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      GANs - Step 2
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      GANs - Step 3
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      GANs - Step 4
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      GANs - Step 5
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      GANs - Step 6
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      GANs - Step 7
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      GANs - Step 8
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      GANs - Step 9
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      GANs - Step 10
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      GANs - Step 11
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      GANs - Step 12
      10m0s
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      Image Creation with GANs
      10m0s
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      Special Thanks to Alexis Jacq
      10m0s
  • 10. Annex 1: Artificial Neural Networks
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      What is Deep Learning?
      10m0s
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      Plan of Attack
      10m0s
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      The Neuron
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      The Activation Function
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      How do Neural Networks work?
      10m0s
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      How do Neural Networks learn?
      10m0s
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      Gradient Descent
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      Stochastic Gradient Descent
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      Backpropagation
      10m0s
  • 11. Annex 2: Convolutional Neural Networks
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      Plan of Attack
      10m0s
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      What are convolutional neural networks?
      10m0s
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      Step 1 - Convolution Operation
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      Step 1(b) - ReLU Layer
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      Step 2 - Pooling
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      Step 3 - Flattening
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      Step 4 - Full Connection
      10m0s
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      Summary
      10m0s
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      Softmax & Cross-Entropy
      10m0s
Authors

Kevin Gautama is a systems design and programming engineer with 16 years of expertise in the fields of electrical and electronics and information technology.

He teaches at the Hanoi University of Industry in the period 2003-2011 and he has a certificate of vocational training by the Ministry of Industry and Commerce and the Hanoi University of Industry.

From extensive design experience through numerous engineering projects, the author founded the Enziin Academy.

The Enziin Academy is a startup in the field of educational, it's core goal is to training design engineers in the fields technology related.

The Enziin Academy is headquartered in Stockholm-Sweden with an orientation operating multi-lingual and global.

The author's skills in IT:

  • Implementing the application infrastructure on Amazon's cloud computing platform.
  • Linux server system administration (Sysadmin).
  • Design load balancing and content distribution system.
  • MySQL database administration.
  • C/C++/C# Programming
  • Ruby and Ruby on Rails Programming
  • Python and Django Programming
  • The WPF/C# on the .NET Framework Programming
  • The PHP/JAVA Programming
  • Machine Learning and Expert System.
  • Internet of Things.

The author's skills in the fields of electric and electronic:

  • The design of popular CPU / MCU systems.
  • Design FPGA / CPLD system (Xilinx - Altera).
  • Design and programming of DSP systems (Texas Instruments).
  • Embedded ARM system design.
  • The RTOS Programming
  • Design and programming electronic power systems.
  • PLC - inverter - sensor - electric control cabinet industrial.
  • Control systems distributed connection with Server.

Read more...

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


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

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