What is Google Deep Dream? (Basic Theory) | Deep Dream Series #1

Aleksa Gordić - The AI Epiphany · Beginner ·📰 AI News & Updates ·5y ago
❤️ Become The AI Epiphany Patreon ❤️ ► https://www.patreon.com/theaiepiphany ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Learn the basic theory behind the Deep Dream algorithm. You'll learn about: ✔️ What Google Deep Dream is and how it all began ✔️Impacts of shallower/deeper layers on the final result ✔️Basic concepts: gradient ascent, image pyramids, etc. ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ ✅ DeepDream in PyTorch: https://github.com/gordicaleksa/pytorch-deepdream ✅ Original blog: https://ai.googleblog.com/2015/06/inceptionism-going-deeper-into-neural.html ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ ⌚️ Timetable: 1:10 - How it all started in 2015 3:30 - Simple explanation of how it works 4:30 - Impact of using shallow layers 5:30 - Dataset matters (ImageNet vs Places 365) 6:10 - More details on how it works ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 💰 BECOME A PATREON OF THE AI EPIPHANY ❤️ If these videos, GitHub projects, and blogs help you, consider helping me out by supporting me on Patreon! The AI Epiphany ► https://www.patreon.com/theaiepiphany One-time donations: https://www.paypal.com/paypalme/theaiepiphany Much love! ❤️ ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 💡 The AI Epiphany is a channel dedicated to simplifying the field of AI using creative visualizations and in general, a stronger focus on geometrical and visual intuition, rather than the algebraic and numerical "intuition". ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 👋 CONNECT WITH ME ON SOCIAL LinkedIn ► https://www.linkedin.com/in/aleksagordic/ Twitter ► https://twitter.com/gordic_aleksa Instagram ► https://www.instagram.com/aiepiphany/ Facebook ► https://www.facebook.com/aiepiphany/ 👨‍👩‍👧‍👦 JOIN OUR DISCORD COMMUNITY: Discord ► https://discord.gg/peBrCpheKE 📢 SUBSCRIBE TO MY MONTHLY AI NEWSLETTER: Substack ► https://aiepiphany.substack.com/ 💻 FOLLOW ME ON GITHUB FOR COOL PROJECTS: GitHub ► https://github.com/gordicaleksa 📚 FOLLOW ME ON MEDIUM: Medium ► https://gordicaleksa.medium.com/ ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ #deepdream #deeplearning #art #ai
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Uploads from Aleksa Gordić - The AI Epiphany · Aleksa Gordić - The AI Epiphany · 10 of 60

1 Intro | Neural Style Transfer #1
Intro | Neural Style Transfer #1
Aleksa Gordić - The AI Epiphany
2 Basic Theory | Neural Style Transfer #2
Basic Theory | Neural Style Transfer #2
Aleksa Gordić - The AI Epiphany
3 Optimization method | Neural Style Transfer #3
Optimization method | Neural Style Transfer #3
Aleksa Gordić - The AI Epiphany
4 Advanced Theory | Neural Style Transfer #4
Advanced Theory | Neural Style Transfer #4
Aleksa Gordić - The AI Epiphany
5 Anyone can make deepfakes now!
Anyone can make deepfakes now!
Aleksa Gordić - The AI Epiphany
6 What is Computer Vision? | The Art of Creating Seeing Machines
What is Computer Vision? | The Art of Creating Seeing Machines
Aleksa Gordić - The AI Epiphany
7 Feed-forward method | Neural Style Transfer #5
Feed-forward method | Neural Style Transfer #5
Aleksa Gordić - The AI Epiphany
8 Alan Turing | Computing Machinery and Intelligence
Alan Turing | Computing Machinery and Intelligence
Aleksa Gordić - The AI Epiphany
9 Feed-forward method (training) | Neural Style Transfer #6
Feed-forward method (training) | Neural Style Transfer #6
Aleksa Gordić - The AI Epiphany
What is Google Deep Dream? (Basic Theory) | Deep Dream Series #1
What is Google Deep Dream? (Basic Theory) | Deep Dream Series #1
Aleksa Gordić - The AI Epiphany
11 Semantic Segmentation in PyTorch | Neural Style Transfer #7
Semantic Segmentation in PyTorch | Neural Style Transfer #7
Aleksa Gordić - The AI Epiphany
12 How to get started with Machine Learning
How to get started with Machine Learning
Aleksa Gordić - The AI Epiphany
13 How to learn PyTorch? (3 easy steps) | 2021
How to learn PyTorch? (3 easy steps) | 2021
Aleksa Gordić - The AI Epiphany
14 PyTorch or TensorFlow?
PyTorch or TensorFlow?
Aleksa Gordić - The AI Epiphany
15 3 Machine Learning Projects For Beginners (Highly visual) | 2021
3 Machine Learning Projects For Beginners (Highly visual) | 2021
Aleksa Gordić - The AI Epiphany
16 Machine Learning Projects (Intermediate level) | 2021
Machine Learning Projects (Intermediate level) | 2021
Aleksa Gordić - The AI Epiphany
17 Cheapest (0$) Deep Learning Hardware Options | 2021
Cheapest (0$) Deep Learning Hardware Options | 2021
Aleksa Gordić - The AI Epiphany
18 How to learn deep learning? (Transformers Example)
How to learn deep learning? (Transformers Example)
Aleksa Gordić - The AI Epiphany
19 How do transformers work? (Attention is all you need)
How do transformers work? (Attention is all you need)
Aleksa Gordić - The AI Epiphany
20 Developing a deep learning project (case study on transformer)
Developing a deep learning project (case study on transformer)
Aleksa Gordić - The AI Epiphany
21 Vision Transformer (ViT) - An image is worth 16x16 words | Paper Explained
Vision Transformer (ViT) - An image is worth 16x16 words | Paper Explained
Aleksa Gordić - The AI Epiphany
22 GPT-3 - Language Models are Few-Shot Learners | Paper Explained
GPT-3 - Language Models are Few-Shot Learners | Paper Explained
Aleksa Gordić - The AI Epiphany
23 Google DeepMind's AlphaFold 2 explained! (Protein folding, AlphaFold 1, a glimpse into AlphaFold 2)
Google DeepMind's AlphaFold 2 explained! (Protein folding, AlphaFold 1, a glimpse into AlphaFold 2)
Aleksa Gordić - The AI Epiphany
24 Attention Is All You Need (Transformer) | Paper Explained
Attention Is All You Need (Transformer) | Paper Explained
Aleksa Gordić - The AI Epiphany
25 Graph Attention Networks (GAT) | GNN Paper Explained
Graph Attention Networks (GAT) | GNN Paper Explained
Aleksa Gordić - The AI Epiphany
26 Graph Convolutional Networks (GCN) | GNN Paper Explained
Graph Convolutional Networks (GCN) | GNN Paper Explained
Aleksa Gordić - The AI Epiphany
27 Graph SAGE - Inductive Representation Learning on Large Graphs | GNN Paper Explained
Graph SAGE - Inductive Representation Learning on Large Graphs | GNN Paper Explained
Aleksa Gordić - The AI Epiphany
28 PinSage - Graph Convolutional Neural Networks for Web-Scale Recommender Systems | Paper Explained
PinSage - Graph Convolutional Neural Networks for Web-Scale Recommender Systems | Paper Explained
Aleksa Gordić - The AI Epiphany
29 OpenAI CLIP - Connecting Text and Images | Paper Explained
OpenAI CLIP - Connecting Text and Images | Paper Explained
Aleksa Gordić - The AI Epiphany
30 Temporal Graph Networks (TGN) | GNN Paper Explained
Temporal Graph Networks (TGN) | GNN Paper Explained
Aleksa Gordić - The AI Epiphany
31 Graph Neural Network Project Update! (I'm coding GAT from scratch)
Graph Neural Network Project Update! (I'm coding GAT from scratch)
Aleksa Gordić - The AI Epiphany
32 Graph Attention Network Project Walkthrough
Graph Attention Network Project Walkthrough
Aleksa Gordić - The AI Epiphany
33 How to get started with Graph ML? (Blog walkthrough)
How to get started with Graph ML? (Blog walkthrough)
Aleksa Gordić - The AI Epiphany
34 DQN - Playing Atari with Deep Reinforcement Learning | RL Paper Explained
DQN - Playing Atari with Deep Reinforcement Learning | RL Paper Explained
Aleksa Gordić - The AI Epiphany
35 AlphaGo - Mastering the game of Go with deep neural networks and tree search | RL Paper Explained
AlphaGo - Mastering the game of Go with deep neural networks and tree search | RL Paper Explained
Aleksa Gordić - The AI Epiphany
36 DeepMind's AlphaGo Zero and AlphaZero | RL paper explained
DeepMind's AlphaGo Zero and AlphaZero | RL paper explained
Aleksa Gordić - The AI Epiphany
37 OpenAI - Solving Rubik's Cube with a Robot Hand | RL paper explained
OpenAI - Solving Rubik's Cube with a Robot Hand | RL paper explained
Aleksa Gordić - The AI Epiphany
38 MuZero - Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model | RL Paper explained
MuZero - Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model | RL Paper explained
Aleksa Gordić - The AI Epiphany
39 EfficientNetV2 - Smaller Models and Faster Training | Paper explained
EfficientNetV2 - Smaller Models and Faster Training | Paper explained
Aleksa Gordić - The AI Epiphany
40 Implementing DeepMind's DQN from scratch! | Project Update
Implementing DeepMind's DQN from scratch! | Project Update
Aleksa Gordić - The AI Epiphany
41 MLP-Mixer: An all-MLP Architecture for Vision | Paper explained
MLP-Mixer: An all-MLP Architecture for Vision | Paper explained
Aleksa Gordić - The AI Epiphany
42 DeepMind's Android RL Environment - AndroidEnv
DeepMind's Android RL Environment - AndroidEnv
Aleksa Gordić - The AI Epiphany
43 When Vision Transformers Outperform ResNets without Pretraining | Paper Explained
When Vision Transformers Outperform ResNets without Pretraining | Paper Explained
Aleksa Gordić - The AI Epiphany
44 Non-Parametric Transformers | Paper explained
Non-Parametric Transformers | Paper explained
Aleksa Gordić - The AI Epiphany
45 Chip Placement with Deep Reinforcement Learning | Paper Explained
Chip Placement with Deep Reinforcement Learning | Paper Explained
Aleksa Gordić - The AI Epiphany
46 Text Style Brush - Transfer of text aesthetics from a single example | Paper Explained
Text Style Brush - Transfer of text aesthetics from a single example | Paper Explained
Aleksa Gordić - The AI Epiphany
47 Graphormer - Do Transformers Really Perform Bad for Graph Representation? | Paper Explained
Graphormer - Do Transformers Really Perform Bad for Graph Representation? | Paper Explained
Aleksa Gordić - The AI Epiphany
48 GANs N' Roses: Stable, Controllable, Diverse Image to Image Translation | Paper Explained
GANs N' Roses: Stable, Controllable, Diverse Image to Image Translation | Paper Explained
Aleksa Gordić - The AI Epiphany
49 VQ-VAEs: Neural Discrete Representation Learning | Paper + PyTorch Code Explained
VQ-VAEs: Neural Discrete Representation Learning | Paper + PyTorch Code Explained
Aleksa Gordić - The AI Epiphany
50 VQ-GAN: Taming Transformers for High-Resolution Image Synthesis | Paper Explained
VQ-GAN: Taming Transformers for High-Resolution Image Synthesis | Paper Explained
Aleksa Gordić - The AI Epiphany
51 Multimodal Few-Shot Learning with Frozen Language Models | Paper Explained
Multimodal Few-Shot Learning with Frozen Language Models | Paper Explained
Aleksa Gordić - The AI Epiphany
52 Focal Transformer: Focal Self-attention for Local-Global Interactions in Vision Transformers
Focal Transformer: Focal Self-attention for Local-Global Interactions in Vision Transformers
Aleksa Gordić - The AI Epiphany
53 AudioCLIP: Extending CLIP to Image, Text and Audio | Paper Explained
AudioCLIP: Extending CLIP to Image, Text and Audio | Paper Explained
Aleksa Gordić - The AI Epiphany
54 RMA: Rapid Motor Adaptation for Legged Robots | Paper Explained
RMA: Rapid Motor Adaptation for Legged Robots | Paper Explained
Aleksa Gordić - The AI Epiphany
55 DALL-E: Zero-Shot Text-to-Image Generation | Paper Explained
DALL-E: Zero-Shot Text-to-Image Generation | Paper Explained
Aleksa Gordić - The AI Epiphany
56 DETR: End-to-End Object Detection with Transformers | Paper Explained
DETR: End-to-End Object Detection with Transformers | Paper Explained
Aleksa Gordić - The AI Epiphany
57 DINO: Emerging Properties in Self-Supervised Vision Transformers | Paper Explained!
DINO: Emerging Properties in Self-Supervised Vision Transformers | Paper Explained!
Aleksa Gordić - The AI Epiphany
58 DeepMind DetCon: Efficient Visual Pretraining with Contrastive Detection | Paper Explained
DeepMind DetCon: Efficient Visual Pretraining with Contrastive Detection | Paper Explained
Aleksa Gordić - The AI Epiphany
59 Do Vision Transformers See Like Convolutional Neural Networks? | Paper Explained
Do Vision Transformers See Like Convolutional Neural Networks? | Paper Explained
Aleksa Gordić - The AI Epiphany
60 Fastformer: Additive Attention Can Be All You Need | Paper Explained
Fastformer: Additive Attention Can Be All You Need | Paper Explained
Aleksa Gordić - The AI Epiphany

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Chapters (5)

1:10 How it all started in 2015
3:30 Simple explanation of how it works
4:30 Impact of using shallow layers
5:30 Dataset matters (ImageNet vs Places 365)
6:10 More details on how it works
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