GAN INTRO 1

What makes Deep Learning “deep”?

• It uses loops in learning

• It learns in the night

• It uses many hidden layers in a neural network

• It runs on deep ocean data

What is the main idea behind a GAN?

• One network backs up data, another restores it

• Two networks compete — one generates, one checks

• One network stores passwords

• It only classifies data into labels

Why do we use a “mini-batch” during training?

• To train on all data at once

• To save memory and update models faster

• To skip training

• To increase model size

What is CycleGAN best used for?

• Translating between image styles (like horse ↔ zebra)

• Finding weather patterns

• Reading documents

• Sending emails

How are GANs helping the fashion industry?

• Sending discount coupons

• Stitching clothes

• Generating new clothing designs from sample patterns

• Counting inventory in stores

In the healthcare industry, what is one common use of GANs?

• Performing surgeries

• Creating fake medical records

• Generating high-quality medical images like MRI from low-quality scans

• Printing prescriptions

In the finance industry, how can GANs help in fraud detection?

• By removing all anomalies

• By generating synthetic fraud examples for training models

• By calculating interest rates

• By replacing accountants

What differentiates Deep Learning from traditional Machine Learning?

• It uses more hardware resources only

• It always uses reinforcement learning

• It automatically learns features through multiple layers

• It doesn't need data

What is one real-world use of GANs in agriculture?

• Controlling irrigation pumps

• Predicting rainfall

• Enhancing satellite imagery for crop health monitoring

• Replacing soil

A gaming company uses GANs to create realistic avatars and fantasy characters based on concept sketches.

Q: What advantage do GANs bring in this gaming use case?

• Reducing game file size

• Enhancing character creation through automatic image generation

• Debugging game code

• Generating game soundtracks