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Image Generation Machine Learning Interview Questions
01 Image Generation Machine Learning Interview Questions
01 What is discriminative modeling (1:00)
02 What is generative modeling (1:10)
Interview Source Files
02 Diffusion Deep Learning Interview Questions
01 What are diffusion models (1:08)
02 How diffusion works in deep learning (2:17)
03 Forward and backward diffusion in ML (1:52)
04 What is a U-Net ML model (1:30)
02b Stable Diffusion Interview Questions
01 Steps of latent reverse diffusion in Stable Diffusion_1 (1:44)
02 What is latent space (3:14)
03 What is the manifold hypothesis in ML (1:39)
03 Dimensionality Reduction Data Science Interview Questions
01 What is dimensionality reduction_1 (1:48)
02 What is principal component analysis (1:16)
04 Autoencoder Machine Learning Interview Questions
01 What are Autoencoders (1:38)
02 What are encoders and decoders in ML (2:13)
03 How do Autoencoders work (2:30)
04 What are Variational Autoencoders (2:59)
05 What is a Vector Quantized Variational Autoencoder (1:45)
05 GAN Neural Network Interview Questions
01 What is the structure of a Generative Adversarial Network_1 (4:17)
02 What are discriminators and generators (3:58)
03 What is zero-shot learning (2:55)
06 Scoring Interview Questions
01 What is Inception Score_1 (3:32)
02 What is Frechet Inception Distance (3:58)
03 How FID Works in ML (1:48)
04 What is Kernel Inception Distance (1:02)
07 Signal Processing Interview Questions
01 What is Time-Series data (1:39)
02 What is signal data (3:40)
03 Continuous signals vs discrete signals (3:12)
04 What is Nyquist rate (1:42)
08 Fourier Analysis Interview Questions
01 What are periodic signals (1:51)
02 What is Fourier Transform (6:58)
05 What is a Vector Quantized Variational Autoencoder
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