Introduction to Deep Learning

Connor Shorten · Beginner ·👁️ Computer Vision ·7y ago
Skills: CV Basics80%

Key Takeaways

The video introduces deep learning concepts, including computer vision, natural language processing, and generative modeling, with applications in self-driving cars, speech recognition, and music generation.

Full Transcript

artificial intelligence technology is more popular than ever thanks to advances in deep learning welcome to Henry AI labs a YouTube channel that explains complex topics and deep learning in artificial intelligence artificial intelligence is currently powered by deep neural networks these are mathematical function approximator xin spired by models of the brain deep neural networks are applied to computer vision natural language processing speech recognition generative modeling geometric deep learning and reinforcement learning computer vision involves applications like having computers to detect what is in an image this involves things like drawing boxes and counting cars or completely segmenting the scene as in self-driving cars additionally these computer vision models are being embedded and compressed into small file sizes so they can fit in embedded systems such as the Raspberry Pi self-driving cars are one of the most exciting applications of the artificial intelligence enabling cars to see perceive and navigate the world around them natural language processing is another really interesting application of deep learning and artificial intelligence NOP models enable statistical models to get an understanding of language this has led to some really amazing applications and sentiment analysis from tweets spam detection on review websites question answering with search engines like Google and others and document summarization another interesting thing is audio speech and music this involves things like speaking into your phone and having it automatically transcribe the text as well as things such as going back from that text to speech recent applications can even synthesized speech in your own voice given some text also interestingly is music generation with advances in music generation being made nearly every month generative modeling is another really cool application of artificial intelligence this includes things like generating images completely from random noise and transferring dance poses and transferring style from one image to another geometric deep learning is another really cool application of deep learning that is becoming more and more popular this involves making sense of graph data things like social network friend recommendations YouTube video recommendations citation networks between scientific papers in protein-protein interaction biological networks reinforcement learning is powering the next generation of game playing a is that learn to play through self play and other methods this is empowering robotics and education technology as well thanks for watching if you're interested in artificial intelligence deep learning please subscribe to Henry AI labs to stay up to date with deep learning research papers thanks for watching

Original Description

Artificial Intelligence powered by Deep Learning is rapidly changing the world! Henry AI Labs makes videos with intuitive explanations of complex topics in Deep Learning as well as videos summarizing recent developments in the field! Please Subscribe, Thanks for Watching! Image Links: https://arxiv.org/pdf/1808.07371.pdf https://arxiv.org/pdf/1812.04948.pdf https://arxiv.org/pdf/1809.11096.pdf https://www.slashgear.com/nvidia-gaugan-neural-network-makes-masterpieces-out-of-doodles-19570191/ https://towardsdatascience.com/a-simple-guide-to-the-versions-of-the-inception-network-7fc52b863202 https://medium.com/@smallfishbigsea/a-walk-through-of-alexnet-6cbd137a5637 https://medium.com/coinmonks/the-artificial-neural-networks-handbook-part-1-f9ceb0e376b4 https://medium.com/@abhigoku10/activation-functions-and-its-types-in-artifical-neural-network-14511f3080a8 https://towardsdatascience.com/semantic-segmentation-popular-architectures-dff0a75f39d0 https://www.analyticsvidhya.com/blog/2018/12/practical-guide-object-detection-yolo-framewor-python/
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Playlist

Uploads from Connor Shorten · Connor Shorten · 24 of 60

1 DenseNets
DenseNets
Connor Shorten
2 DeepWalk Explained
DeepWalk Explained
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3 Inception Network Explained
Inception Network Explained
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4 StackGAN
StackGAN
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5 StyleGAN
StyleGAN
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6 Progressive Growing of GANs Explained
Progressive Growing of GANs Explained
Connor Shorten
7 Improved Techniques for Training GANs
Improved Techniques for Training GANs
Connor Shorten
8 Word2Vec Explained
Word2Vec Explained
Connor Shorten
9 Must Read Papers on GANs
Must Read Papers on GANs
Connor Shorten
10 Unsupervised Feature Learning
Unsupervised Feature Learning
Connor Shorten
11 Self-Supervised GANs
Self-Supervised GANs
Connor Shorten
12 Embedding Graphs with Deep Learning
Embedding Graphs with Deep Learning
Connor Shorten
13 Transfer Learning in GANs
Transfer Learning in GANs
Connor Shorten
14 ReLU Activation Function
ReLU Activation Function
Connor Shorten
15 AC-GAN Explained
AC-GAN Explained
Connor Shorten
16 SimGAN Explained
SimGAN Explained
Connor Shorten
17 DC-GAN Explained!
DC-GAN Explained!
Connor Shorten
18 ResNet Explained!
ResNet Explained!
Connor Shorten
19 Graph Convolutional Networks
Graph Convolutional Networks
Connor Shorten
20 Neural Architecture Search
Neural Architecture Search
Connor Shorten
21 Henry AI Labs
Henry AI Labs
Connor Shorten
22 Video Classification with Deep Learning
Video Classification with Deep Learning
Connor Shorten
23 BigGANs in Data Augmentation
BigGANs in Data Augmentation
Connor Shorten
Introduction to Deep Learning
Introduction to Deep Learning
Connor Shorten
25 EfficientNet Explained!
EfficientNet Explained!
Connor Shorten
26 Self-Attention GAN
Self-Attention GAN
Connor Shorten
27 Curriculum Learning in Deep Neural Networks
Curriculum Learning in Deep Neural Networks
Connor Shorten
28 Deep Learning Podcast #1 | Edward Dixon | Stochastic Weight Averaging
Deep Learning Podcast #1 | Edward Dixon | Stochastic Weight Averaging
Connor Shorten
29 Deep Compression
Deep Compression
Connor Shorten
30 Skin Cancer Classification with Deep Learning
Skin Cancer Classification with Deep Learning
Connor Shorten
31 Deep Learning Podcast #2 | Edward Peake | Deep Learning in Medical Imaging
Deep Learning Podcast #2 | Edward Peake | Deep Learning in Medical Imaging
Connor Shorten
32 The Lottery Ticket Hypothesis Explained!
The Lottery Ticket Hypothesis Explained!
Connor Shorten
33 SqueezeNet
SqueezeNet
Connor Shorten
34 GauGAN Explained!
GauGAN Explained!
Connor Shorten
35 AutoML with Hyperband
AutoML with Hyperband
Connor Shorten
36 DL Podcast #3 | Yannic Kilcher | Population-Based Search
DL Podcast #3 | Yannic Kilcher | Population-Based Search
Connor Shorten
37 Weakly Supervised Pretraining
Weakly Supervised Pretraining
Connor Shorten
38 Image Data Augmentation for Deep Learning
Image Data Augmentation for Deep Learning
Connor Shorten
39 Unsupervised Data Augmentation
Unsupervised Data Augmentation
Connor Shorten
40 Wide ResNet Explained!
Wide ResNet Explained!
Connor Shorten
41 RevNet: Backpropagation without Storing Activations
RevNet: Backpropagation without Storing Activations
Connor Shorten
42 GANs with Fewer Labels
GANs with Fewer Labels
Connor Shorten
43 BigBiGAN Unsupervised Learning!
BigBiGAN Unsupervised Learning!
Connor Shorten
44 Self-Supervised Learning
Self-Supervised Learning
Connor Shorten
45 Multi-Task Self-Supervised Learning
Multi-Task Self-Supervised Learning
Connor Shorten
46 Self-Supervised GANs
Self-Supervised GANs
Connor Shorten
47 Population Based Training
Population Based Training
Connor Shorten
48 Show, Attend and Tell
Show, Attend and Tell
Connor Shorten
49 Siamese Neural Networks
Siamese Neural Networks
Connor Shorten
50 WaveGAN Explained!
WaveGAN Explained!
Connor Shorten
51 VAE-GAN Explained!
VAE-GAN Explained!
Connor Shorten
52 Evolution in Neural Architecture Search!
Evolution in Neural Architecture Search!
Connor Shorten
53 AI Research Weekly Update August 18th, 2019
AI Research Weekly Update August 18th, 2019
Connor Shorten
54 Weight Agnostic Neural Networks Explained!
Weight Agnostic Neural Networks Explained!
Connor Shorten
55 AI Research Weekly Update August 25th, 2019
AI Research Weekly Update August 25th, 2019
Connor Shorten
56 Neuroevolution of Augmenting Topologies (NEAT)
Neuroevolution of Augmenting Topologies (NEAT)
Connor Shorten
57 CoDeepNEAT
CoDeepNEAT
Connor Shorten
58 AI Research Weekly Update September 1st, 2019
AI Research Weekly Update September 1st, 2019
Connor Shorten
59 Randomly Wired Neural Networks
Randomly Wired Neural Networks
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60 Genetic CNN
Genetic CNN
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This video introduces deep learning concepts and applications, including computer vision, natural language processing, and generative modeling, with a focus on beginner-friendly explanations.

Key Takeaways
  1. Learn the basics of deep learning
  2. Understand computer vision applications
  3. Explore natural language processing and generative modeling
  4. Discover geometric deep learning and reinforcement learning
  5. Apply deep learning concepts to real-world problems
💡 Deep learning is a powerful technology with various applications, including computer vision, natural language processing, and generative modeling, which can be applied to real-world problems.

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