Emotion AI: Facial Key-points Detection

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In this Guided Project, you will:

Understand the theory and intuition behind Deep Neural Networks, and Residual Neural Networks, and Convolutional Neural Networks (CNNs).

Build and train a deep learning model based on Convolutional Neural Network and Residual blocks using Keras with Tensorflow 2.0 as a backend.

Assess the performance of trained CNN and ensure its generalization using various Key performance indicators.

3 hours
Intermediate
No download needed
Split-screen video
English
Desktop only

In this 1-hour long project-based course, you will be able to: - Understand the theory and intuition behind Deep Learning, Convolutional Neural Networks (CNNs) and Residual Neural Networks. - Import Key libraries, dataset and visualize images. - Perform data augmentation to increase the size of the dataset and improve model generalization capability. - Build a deep learning model based on Convolutional Neural Network and Residual blocks using Keras with Tensorflow 2.0 as a backend. - Compile and fit Deep Learning model to training data. - Assess the performance of trained CNN and ensure its generalization using various KPIs. - Improve network performance using regularization techniques such as dropout.

Skills you will develop

  • Deep Learning

  • Machine Learning

  • Python Programming

  • Artificial Intelligence(AI)

  • Computer Vision

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Task 1: Project Overview/Understand the problem statement and business case

  2. Task 2: Import Libraries/datasets and perform preliminary data processing

  3. Task 3: Perform Image Visualization

  4. Task 4: Perform Image Augmentation

  5. Task 5: Prepare the data for deep learning model training (Normalization/reshaping)

  6. Task 6: Understand the theory and intuition behind Deep Neural Networks and CNNs.

  7. Task 7: Build Deep Residual Neural Network Model

  8. Task 8: Compile and train deep learning model

  9. Task 9: Assess the Performance of the Trained Model

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Instructor

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Frequently Asked Questions

By purchasing a Guided Project, you'll get everything you need to complete the Guided Project including access to a cloud desktop workspace through your web browser that contains the files and software you need to get started, plus step-by-step video instruction from a subject matter expert.

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At the top of the page, you can press on the experience level for this Guided Project to view any knowledge prerequisites. For every level of Guided Project, your instructor will walk you through step-by-step.

Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.

You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.

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