🗜️ An Overview Of Autoencoders

Autoencoders are used in various applications, including fraud detection, predictive maintenance, image processing, etc. This session will give you a comprehensive overview of autoencoders. It will go over key concepts, model architectures, and training methods. Beginner to experienced individuals can all benefit from this focus on applicable skills development.

What Will Be Covered

In this session, you will,

• Get an overview of autoencoders.
• Understand what is meant by latent spaces.
• Gain an understanding of the architecture of a basic autoencoder (encoder, latent space and decoder).
• Get an overview of autoencoder training (loss functions, regularization techniques).
• Get an overview of Variational Autoencoders (VAEs) - how they are trained, the reparameterization trick, KL-divergence loss, applications of VAEs
• Learn how VAEs can be used for dimensionality reduction.
• Get an overview of different types of autoencoders (Convolutional Autoencoders, Denoising Autoencoder, etc.)
• Get an overview of real-world use cases of autoencoders.
• Gain hands-on experience with autoencoders for a real-world use case.

Hands-On Session

We will use Google Colab notebooks to simplify the process by eliminating the need to install prerequisite libraries.

🖼️ The required dataset of images will be shared during the session.

Upcoming Sessions

Please note:

• All times above are expressed in SGT. Click on the 🌏 icon next to sessions of interest to get your location’s corresponding date and time.
• For reference, 9 PM SGT is 6:30 PM (Bangalore), 8 PM (Jakarta), 6 PM (Lahore)

Other Dates & Times

👋 I am interested but don’t see a date or time that works for me.

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What’s Next?

What’s next after attending this session?

Check out the complete list of upcoming sessions.

Alternatively, if you are a hands-on creator, check out the upcoming Hands-On Learning Sessions.