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Generative Deep Learning Updated Edition

15 chapters and 72 canonical sections synced from the Cuantum content database.

Author
Cuantum Tech.
Chapters
15
Reading time
~ 14h
Level
Professional
Language
English
Edition
2025
Your progress0%
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Chapters & sections

15 chapters - 72 sections
Chapter 01

Chapter 1: Introduction to Deep Learning

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11.1 Basics of Neural Networks12m21.2 Overview of Deep Learning12m31.3 Recent Advances in Deep Learning12m41.4 Practical Exercises - Chapter 1: Introduction to Deep Learning12m51.5 Chapter Summary - Chapter 1: Introduction to Deep Learning12m
Chapter 02

Chapter 2: Understanding Generative Models

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12.1 Concept and Importance12m22.2 Delve Deeper into Types of Generative Models12m32.3 Recent Developments in Generative Models12m42.4 Practical Exercises - Chapter 2: Understanding Generative Models12m52.5 Chapter 2 Summary - Chapter 2: Understanding Generative Models12m
Chapter 03

Quiz: Foundations of Deep Learning

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3Answers - Quiz: Foundations of Deep Learning12m1Questions of Chapter 1: Introduction to Deep Learning12m2Questions of Chapter 2: Understanding Generative Models12m
Chapter 04

Chapter 3: Deep Dive into Generative Adversarial Networks (GANs)

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13.1 Understanding GANs12m23.2 Architecture of GANs12m33.3 Training GANs12m43.4 Evaluating GANs12m53.5 Variations of GANs12m63.6 Use Cases and Applications of GANs12m73.7 Recent Innovations in GANs12m83.8 Practical Exercises - Chapter 3: Deep Dive into Generative Adversarial Networks (GANs)12m93.9 Chapter Summary - Chapter 3: Deep Dive into Generative Adversarial Networks (GANs)12m
Chapter 05

Chapter 4: Project Face Generation with GANs

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14.1 Data Collection and Preprocessing12m24.2 Model Creation12m34.3 Training the GAN12m44.4 Generating New Faces12m54.5 Evaluating the Model12m64.6 Enhancing Face Generation with StyleGAN12m74.7 Chapter Summary - Chapter 4: Project Face Generation with GANs12m
Chapter 06

Quiz: Generative Adversarial Networks (GAN)

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3Answers - Quiz: Generative Adversarial Networks (GAN)12m1Questions - Chapter 3: Deep Dive into Generative Adversarial Networks (GANs)12m2Questions - Chapter 4: Project: Face Generation with GANs12m
Chapter 07

Chapter 5: Exploring Variational Autoencoders (VAEs)

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15.1 Understanding VAEs12m25.2 Architecture of VAEs12m45.3 Training VAEs12m35.3 Training VAEs12m55.5 Variations of VAEs (Beta-VAE, Conditional VAE)12m65.6 Use Cases and Applications of VAEs12m75.7 Recent Advances in VAEs12m85.8 Practical Exercises - Chapter 5: Exploring Variational Autoencoders (VAEs)12m95.9 Chapter Summary - Chapter 5: Exploring Variational Autoencoders (VAEs)12m
Chapter 08

Chapter 6: Project: Handwritten Digit Generation with VAEs

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16.1 Data Collection and Preprocessing12m26.2 Model Creation12m36.3 Generating New Handwritten Digits12m46.4 Evaluating the Model12m56.5 Enhancing Digit Generation with Beta-VAE12m
Chapter 09

Quiz: Variational Autoencoders (VAEs)

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2Answers - Quiz: Variational Autoencoders (VAEs)12m1Questions - Quiz: Variational Autoencoders (VAEs)12m
Chapter 10

Chapter 7: Understanding Autoregressive Models

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17.1 PixelRNN and PixelCNN12m27.2 Transformer-based Models (GPT, GPT-3, GPT-4)12m37.3 Use Cases and Applications of Autoregressive Models12m47.4 Practical Exercises - Chapter 7: Understanding Autoregressive Models12m57.5 Chapter Summary - Chapter 7: Understanding Autoregressive Models12m
Chapter 11

Chapter 8: Project: Text Generation with Autoregressive Models

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18.1 Data Collection and Preprocessing12m28.2 Model Creation12m38.3 Generating Text with the Fine-Tuned Model12m48.4 Evaluating the Model12m
Chapter 12

Quiz: Autoregressive Models

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2Answers - Quiz: Autoregressive Models12m1Questions - Quiz: Autoregressive Models12m
Chapter 13

Chapter 9: Exploring Diffusion Models

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19.1 Understanding Diffusion Models12m29.2 Architecture of Diffusion Models12m39.3 Training Diffusion Models12m49.4 Evaluating Diffusion Models12m59.5 Practical Exercises - Chapter 9: Exploring Diffusion Models12m69.6 Chapter Summary - Chapter 9: Exploring Diffusion Models12m
Chapter 14

Chapter 10: Project: Image Generation with Diffusion Models

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110.1 Data Collection and Preprocessing12m210.2 Model Creation12m310.3 Training the Diffusion Model12m410.4 Generating New Images12m510.5 Evaluating the Model12m
Chapter 15

Quiz: Diffusion Models of the book which includes

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2Answers - Quiz: Diffusion Models of the book which includes12m1Questions - Quiz: Diffusion Models of the book which includes12m