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.
Showcase this hands-on experience in an interview
In this hands-on project, we will train a deep learning model based on Convolutional Neural Networks (CNNs) and Residual Blocks to detect facial expressions. This project could be practically used for detecting customer emotions and facial expressions. By the end of this project, 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.
Basic python programming and mathematics
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Project Overview/Understand the problem statement and business case
Import Libraries/datasets and perform preliminary data processing
Perform Image Visualization
Perform Image Augmentation, normalization and splitting
Understand the theory and intuition behind Deep Neural Networks and CNNs
Build and Train Residual Neural Network Model
Assess the Performance of the Trained Model
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
Wonderful course! I got a lot of new knowledge, particularly about how CNN really works and how to apply it using existing libraries in python! 6/5
Easy Quiz thanks for this course it helped me to understand concept clearly without wasting much of my time.
Good course , for a short and introductory portion for a bigger work.
the lecturer is so geniuuuuuuussss, thank you so much
Are Guided Projects available on desktop and mobile?
Because your workspace contains a cloud desktop that is sized for a laptop or desktop computer, Guided Projects are not available on your mobile device.
Who are the instructors for Guided Projects?
Guided Project instructors are subject matter experts who have experience in the skill, tool or domain of their project and are passionate about sharing their knowledge to impact millions of learners around the world.
Can I download the work from my Guided Project after I complete it?
You can download and keep any of your created files from the Guided Project. To do so, you can use the “File Browser” feature while you are accessing your cloud desktop.
How much experience do I need to do this Guided Project?
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.
Can I complete this Guided Project right through my web browser, instead of installing special software?
Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.
What is the learning experience like with Guided Projects?
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.
More questions? Visit the Learner Help Center.