the fundamentals of deep learning
play

The Fundamentals of Deep Learning Building Blocks Theory with - PowerPoint PPT Presentation

Jan 20, 2023 •18 likes •1.08k views

Deep Learning Antecedents Vision Case Study The Fundamentals of Deep Learning Building Blocks Theory with Applications Neural Units Neural Nets Deep Neural Nets Application ConvNets Jon Krohn LSTMs untapt jon@untapt.com

  1. Deep Learning Multi-Layer Perceptron Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  2. Deep Learning Sigmoid Neuron Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  3. Deep Learning tanh Neuron Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  4. Deep Learning ReLU: Rectified Linear Units Nair & Hinton (2010); Maas, Hannun & Ng (2014) Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  5. Deep Learning Outline Antecedents Vision Case Study Antecedents 1 Building Blocks Theory Case Study: A History of Biological & Artificial Vision Neural Units Building Blocks Neural Nets Deep Neural Nets Application 2 Theory ConvNets LSTMs Biological & Artificial Neurons untapt Reinforcement Neural Networks Deep Neural Networks Contemporary Applications 3 Convolutional Neural Networks Long Short-Term Memory Recurrent Neural Networks Deep Learning at untapt Deep Reinforcement Learning

  6. Deep Learning MNIST LeCun, Cortes & Burges Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  7. Deep Learning Fully-Connected Neural Net Single Hidden Layer Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  8. Deep Learning TensorFlow Playground Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt [demo] Reinforcement

  9. Deep Learning Outline Antecedents Vision Case Study Antecedents 1 Building Blocks Theory Case Study: A History of Biological & Artificial Vision Neural Units Building Blocks Neural Nets Deep Neural Nets Application 2 Theory ConvNets LSTMs Biological & Artificial Neurons untapt Reinforcement Neural Networks Deep Neural Networks Contemporary Applications 3 Convolutional Neural Networks Long Short-Term Memory Recurrent Neural Networks Deep Learning at untapt Deep Reinforcement Learning

  10. Deep Learning Deep Fully-Connected Net 3 (or more) Hidden Layers Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  11. Deep Learning TFLearn Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application Caffe Torch Theano TensorFlow ConvNets Language C++, Python Lua Python Python LSTMs untapt Pretrained Yes++ Yes++ Yes (Lasagne) Inception Reinforcement Parallel GPUs: Data Yes Yes Yes Yes Parallel GPUs: Model No Yes Experimental Yes (best) Readable Source Code Yes (C++) Yes No No Good at RNN No Mediocre Yes Yes (best) Higher-Level APIs No No Keras Keras and TFLearn

  12. Deep Learning A Simple Deep Net in TFLearn Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt [notebook] Reinforcement

  13. Deep Learning Synaptic Pruning Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  14. Deep Learning (Stochastic) Gradient Descent Adam = AdaGrad + RMSprop Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  15. Deep Learning Backpropagation computes error & gradient of cost function Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  16. Deep Learning Overfitting ...and avoiding it Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement • L1/L2 regularization • dropout • artificial data set expansion

  17. Deep Learning Improving Neural Networks Mostly Hyperparameter Tuning Antecedents Vision Case Study Building Blocks Theory • problem simplification Neural Units Neural Nets Deep Neural Nets • number and width of layers Application • cost fxn: quadratic, cross-entropy, log-likelihood, &c. ConvNets LSTMs untapt • more epochs, early stopping Reinforcement • clever initialization of weights and biases • learning rate η , variable schedule • regularization parameter λ • mini-batch size • automation, e.g., with Spearmint [Summary Blog Post]

  18. Deep Learning Universality Solve Any Continuous Function (Nielsen, 2015) Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  19. Deep Learning Unstable Gradient Typically Vanishes (but can Explode ) Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  20. Deep Learning Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  21. Deep Learning Classic Deep Architectures ...introducing Convolutional Layers Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  22. Deep Learning Outline Antecedents Vision Case Study Antecedents 1 Building Blocks Theory Case Study: A History of Biological & Artificial Vision Neural Units Building Blocks Neural Nets Deep Neural Nets Application 2 Theory ConvNets LSTMs Biological & Artificial Neurons untapt Reinforcement Neural Networks Deep Neural Networks Contemporary Applications 3 Convolutional Neural Networks Long Short-Term Memory Recurrent Neural Networks Deep Learning at untapt Deep Reinforcement Learning

  23. Deep Learning Hubel & Wiesel (1959) Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  24. Deep Learning Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  25. Deep Learning Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  26. Deep Learning AlexNet Krizhevsky, Sutskever & Hinton (2012) Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  27. Deep Learning Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  28. Deep Learning ConvNet Visualisation Yosinski et al. (2015) Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement [video]

  29. Deep Learning Network Architectures Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  30. Deep Learning AlexNet: ILSVRC ‘12 winner Krizhevsky et al. (2012) Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement [TFLearn notebook]

  31. Deep Learning VGGNet: ILSVRC ‘14 runner-up Simonyan & Zisserman (2015) Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement [TFLearn notebook]

  32. Deep Learning ConvNet in TensorFlow Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application Caffe Torch Theano TensorFlow ConvNets Language C++, Python Lua Python Python LSTMs untapt Pretrained Yes++ Yes++ Yes (Lasagne) Inception Reinforcement Parallel GPUs: Data Yes Yes Yes Yes Parallel GPUs: Model No Yes Experimental Yes (best) Readable Source Code Yes (C++) Yes No No Good at RNN No Mediocre Yes Yes (best) Higher-Level APIs No No Keras Keras and TFLearn

  33. Deep Learning ConvNet in TensorFlow Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt [notebook] Reinforcement

  34. Deep Learning Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  35. Deep Learning ConvNet in Theano Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application Caffe Torch Theano TensorFlow ConvNets Language C++, Python Lua Python Python LSTMs untapt Pretrained Yes++ Yes++ Yes (Lasagne) Inception Reinforcement Parallel GPUs: Data Yes Yes Yes Yes Parallel GPUs: Model No Yes Experimental Yes (best) Readable Source Code Yes (C++) Yes No No Good at RNN No Mediocre Yes Yes (best) Higher-Level APIs No No Keras Keras and TFLearn

  36. Deep Learning ConvNet in Theano Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt [demo] Reinforcement

  37. Deep Learning ConvNet in Keras calls TensorFlow or Theano Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets Caffe Torch Theano TensorFlow LSTMs untapt Language C++, Python Lua Python Python Reinforcement Pretrained Yes++ Yes++ Yes (Lasagne) Inception Parallel GPUs: Data Yes Yes Yes Yes Parallel GPUs: Model No Yes Experimental Yes (best) Readable Source Code Yes (C++) Yes No No Good at RNN No Mediocre Yes Yes (best) Higher-Level APIs No No Keras Keras and TFLearn

  38. Deep Learning ConvNet in Keras calls TensorFlow or Theano Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement [notebook]

  39. Deep Learning “2.5-dimension” CT Scans Roth et al. (2015) Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  40. Deep Learning Computer-Aided Detection Shin et al. (2016); Roth et al. (2016) Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  41. Deep Learning Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  42. Deep Learning Kaggle Data Science Bowl 2017 Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement [link]

  43. Deep Learning Transfer Learning Caffe Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets Caffe Torch Theano TensorFlow LSTMs untapt Language C++, Python Lua Python Python Reinforcement Pretrained Yes++ Yes++ Yes (Lasagne) Inception Parallel GPUs: Data Yes Yes Yes Yes Parallel GPUs: Model No Yes Experimental Yes (best) Readable Source Code Yes (C++) Yes No No Good at RNN No Mediocre Yes Yes (best) Higher-Level APIs No No Keras Keras and TFLearn

  44. Deep Learning Transfer Learning Caffe Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement [Model Zoo]

  45. Deep Learning Transfer Learning Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  46. Deep Learning Video Classification Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt [video] Reinforcement

  47. Deep Learning Outline Antecedents Vision Case Study Antecedents 1 Building Blocks Theory Case Study: A History of Biological & Artificial Vision Neural Units Building Blocks Neural Nets Deep Neural Nets Application 2 Theory ConvNets LSTMs Biological & Artificial Neurons untapt Reinforcement Neural Networks Deep Neural Networks Contemporary Applications 3 Convolutional Neural Networks Long Short-Term Memory Recurrent Neural Networks Deep Learning at untapt Deep Reinforcement Learning

  48. Deep Learning Sunspring Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  49. Deep Learning Sunspring Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  50. Deep Learning Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  51. Deep Learning Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  52. Deep Learning RNNs; LSTM RNNs Hochreiter & Schmidhuber (1997) Antecedents Graves, ... & Schmidhuber (2009) Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  53. Deep Learning Vector Space Embedding Word2Vec: Mikolov, ... & Dean (2013) Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  54. Deep Learning t-SNE Hinton & van der Maaten (2008) Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  55. Deep Learning Word2Vec + t-SNE Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  56. Deep Learning Word2Vec + t-SNE Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  57. Deep Learning ‘Understand’ Language with Word2Vec features in your model Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement [even with small corpora]

  58. Deep Learning Quick, Draw! ConvNet + LSTM Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement [link]

  59. Deep Learning Outline Antecedents Vision Case Study Antecedents 1 Building Blocks Theory Case Study: A History of Biological & Artificial Vision Neural Units Building Blocks Neural Nets Deep Neural Nets Application 2 Theory ConvNets LSTMs Biological & Artificial Neurons untapt Reinforcement Neural Networks Deep Neural Networks Contemporary Applications 3 Convolutional Neural Networks Long Short-Term Memory Recurrent Neural Networks Deep Learning at untapt Deep Reinforcement Learning

  60. Deep Learning untapt Digital Recruitment Platform Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  61. Deep Learning untapt Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  62. Deep Learning untapt Candidate-Side Feedback Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  63. Deep Learning untapt Client-Side Feedback Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement

  64. Deep Learning untapt Multi-Stage Bayesian Regression with PyMC3 Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement Krohn, Rives-Corbett & Donner (2016)

  65. Deep Learning untapt Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement Krohn, Rives-Corbett & Donner (2016)

  66. Deep Learning untapt Ensemble with Deep Neural Net Antecedents Vision Case Study Building Blocks Theory Neural Units Neural Nets Deep Neural Nets Application ConvNets LSTMs untapt Reinforcement deep-orange.untapt.com

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend

BBM413 Fundamentals of Image Processing Introduction to Deep Learning Erkut Erdem

BBM413 Fundamentals of Image Processing Introduction to Deep Learning Erkut Erdem

BBM413 Fundamentals of Image Processing Introduction to Deep Learning Erkut Erdem Hacettepe University Computer Vision Lab (HUCVL) What is deep learning? Y. LeCun, Y. Bengio, G. Hinton, "Deep Learning" , Nature,

1.12k views • 84 slides
FUNDAMENTALS OF DEEP LEARNING FOR COMPUTER VISION Twin Karmakharm DLI Certified Instructor

FUNDAMENTALS OF DEEP LEARNING FOR COMPUTER VISION Twin Karmakharm DLI Certified Instructor

FUNDAMENTALS OF DEEP LEARNING FOR COMPUTER VISION Twin Karmakharm DLI Certified Instructor This event is organised and run by... What we do: Project work and consultancy Training Deep Learning, HPC, GPU Deep Learning

651 views • 32 slides
BBM406 Fundamentals of Machine Learning Lecture 13: Introduction to Deep Learning Aykut

BBM406 Fundamentals of Machine Learning Lecture 13: Introduction to Deep Learning Aykut

Illustration: Illustration: Benedetto Cristofani BBM406 Fundamentals of Machine Learning Lecture 13: Introduction to Deep Learning Aykut Erdem // Hacettepe University // Fall 2019 A reminder about course projects From now on, regular

899 views • 51 slides
BBM406 Fundamentals of Machine Learning Lecture 14: Deep Convolutional Networks Aykut Erdem

BBM406 Fundamentals of Machine Learning Lecture 14: Deep Convolutional Networks Aykut Erdem

Illustration:detail from the visualization of ResNet-50 conv2 // Graphcore BBM406 Fundamentals of Machine Learning Lecture 14: Deep Convolutional Networks Aykut Erdem // Hacettepe University // Fall 2019 Announcement Midterm exam on Nov

1.38k views • 121 slides
Hao Su July 6, 2017 Outline Overview of 3D deep learning 3D deep learning algorithms

Hao Su July 6, 2017 Outline Overview of 3D deep learning 3D deep learning algorithms

Deep 3D Representation Learning for Visual Computing Hao Su July 6, 2017 Outline Overview of 3D deep learning 3D deep learning algorithms Conclusion 2 Outline Overview of 3D deep learning Background 3D deep learning tasks 3D deep

1.66k views • 122 slides
ACCELERATE DEEP LEARNING WITH NVIDIA'S DEEP LEARNING PLATFORM | STEPHEN JONES | GTC16 DEEP

ACCELERATE DEEP LEARNING WITH NVIDIA'S DEEP LEARNING PLATFORM | STEPHEN JONES | GTC16 DEEP

ACCELERATE DEEP LEARNING WITH NVIDIA'S DEEP LEARNING PLATFORM | STEPHEN JONES | GTC16 DEEP LEARNING EVERYWHERE INTERNET & CLOUD MEDICINE & BIOLOGY MEDIA & ENTERTAINMENT SECURITY & DEFENSE AUTONOMOUS MACHINES Image

307 views • 26 slides
Deep Learning on GPUs March 2016 What is Deep Learning? GPUs and DL AGENDA DL in practice

Deep Learning on GPUs March 2016 What is Deep Learning? GPUs and DL AGENDA DL in practice

Deep Learning on GPUs March 2016 What is Deep Learning? GPUs and DL AGENDA DL in practice Scaling up DL 2 What is Deep Learning? 3 DEEP LEARNING EVERYWHERE INTERNET & CLOUD MEDICINE & BIOLOGY SECURITY & DEFENSE MEDIA &

1.45k views • 39 slides
Reproducibility and Replicability in Deep Reinforcement Learning (and Other Deep Learning

Reproducibility and Replicability in Deep Reinforcement Learning (and Other Deep Learning

Reproducibility and Replicability in Deep Reinforcement Learning (and Other Deep Learning Methods) Peter Henderson Statistical Society of Canada Annual Meeting 2018 Contributors Riashat Islam Phil Bachman Doina Precup David Meger Joelle

850 views • 37 slides
Image Classification with DIGITS NVIDIA Deep Learning Institute 1 DEEP LEARNING INSTITUTE DLI

Image Classification with DIGITS NVIDIA Deep Learning Institute 1 DEEP LEARNING INSTITUTE DLI

Image Classification with DIGITS NVIDIA Deep Learning Institute 1 DEEP LEARNING INSTITUTE DLI Mission Helping people solve challenging problems using AI and deep learning. Developers, data scientists and engineers Self-driving cars,

1.44k views • 72 slides
Deep Neural Networks and Deep Reinforcement Learning Deep Learning, Goodfellow, Bengio and

Deep Neural Networks and Deep Reinforcement Learning Deep Learning, Goodfellow, Bengio and

Deep Neural Networks and Deep Reinforcement Learning Deep Neural Networks and Deep Reinforcement Learning Deep Learning, Goodfellow, Bengio and Courville [chapt. 6,7,8]; AIMA [sect. 21.1-21.3]; Sutton and Barto, Reinforcement Learning: an

527 views • 35 slides
Natural Language Processing with Deep Learning CS224N The Future of Deep Learning + NLP Kevin

Natural Language Processing with Deep Learning CS224N The Future of Deep Learning + NLP Kevin

Natural Language Processing with Deep Learning CS224N The Future of Deep Learning + NLP Kevin Clark Deep Learning for NLP 5 years ago No Seq2Seq No Attention No large-scale QA/reading comprehension datasets No TensorFlow or

1.41k views • 92 slides
An Overview of Deep Residual Learning Semih Yagcioglu 01.03.2016 Deep Residual Learning

An Overview of Deep Residual Learning Semih Yagcioglu 01.03.2016 Deep Residual Learning

An Overview of Deep Residual Learning Semih Yagcioglu 01.03.2016 Deep Residual Learning Microsoft Research Asia (MSRA) Kaiming He, Xiangyu Zhang, Shaoqing Ren, & Jian Sun. Deep Residual Learning for Image Recognition. arXiv

1.32k views • 54 slides
Deep Reinforcement Learning [Mastering the Game of Go with Deep Reinforcement Learning and Tree

Deep Reinforcement Learning [Mastering the Game of Go with Deep Reinforcement Learning and Tree

Deep Reinforcement Learning [Mastering the Game of Go with Deep Reinforcement Learning and Tree Search, Nature 2016] CS 486/686 University of Waterloo Lecture 21: July 12, 2017 Outline AlphaGo Supervised Learning of Policy Networks

540 views • 15 slides
Mocha.jl Deep Learning in Julia Chiyuan Zhang (@pluskid) CSAIL, MIT Deep Learning Learning

Mocha.jl Deep Learning in Julia Chiyuan Zhang (@pluskid) CSAIL, MIT Deep Learning Learning

Mocha.jl Deep Learning in Julia Chiyuan Zhang (@pluskid) CSAIL, MIT Deep Learning Learning with multi-layer (3~30) neural networks, on a huge training set. State-of-the-art on many AI tasks Computer Vision : Image Classification,

1.53k views • 23 slides
Minjie Wang Deep Learning Deep Learning trend in the past 10 years Caffe State-of-art DL

Minjie Wang Deep Learning Deep Learning trend in the past 10 years Caffe State-of-art DL

Tofu: Parallelizing Deep Learning Systems with Automatic Tiling Minjie Wang Deep Learning Deep Learning trend in the past 10 years Caffe State-of-art DL system is based on dataflow GPU#0 w1 w2 data g1 g2 Forward propagation

405 views • 38 slides
Deep Learning: Theory and Practice Deep Learning - Practical 02-04-2020 Considerations

Deep Learning: Theory and Practice Deep Learning - Practical 02-04-2020 Considerations

Deep Learning: Theory and Practice Deep Learning - Practical 02-04-2020 Considerations deeplearning.cce2020@gmail.com Deep Networks Intuition Neural networks with multiple hidden layers - Deep networks [Hinton, 2006] Deep Networks Intuition

1.33k views • 28 slides
User Interface Design 1 User Interface Design Think of examples Good examples, personal

User Interface Design 1 User Interface Design Think of examples Good examples, personal

User Interface Design 1 User Interface Design Think of examples Good examples, personal favorites, smart UIs Poor examples, the ones you really hate to use and reasons for your verdict 2 This Lecture Cover some basics of

1.16k views • 54 slides
Cognitive Load Theory Why is learning to code so hard? What is cognitive load theory? Memory

Cognitive Load Theory Why is learning to code so hard? What is cognitive load theory? Memory

Cognitive Load Theory Why is learning to code so hard? What is cognitive load theory? Memory https://learndojo.org/wp-content/uploads/2019/02/multistore-memory-model.png Long term memory Beginner Schema

199 views • 16 slides
Recurrent Neural Networks (RNN) Artificial Intelligence @ Allegheny College Janyl Jumadinova

Recurrent Neural Networks (RNN) Artificial Intelligence @ Allegheny College Janyl Jumadinova

Recurrent Neural Networks (RNN) Artificial Intelligence @ Allegheny College Janyl Jumadinova March 9, 2020 Alex Graves, Supervised Sequence Labelling with Recurrent Neural Networks http://colah.github.io/posts/2015-08-Understanding-LSTMs/

538 views • 18 slides
Deep Recurrent Q-Learning for Partially Observable MDPs Matthew Hausknecht and Peter Stone

Deep Recurrent Q-Learning for Partially Observable MDPs Matthew Hausknecht and Peter Stone

Deep Recurrent Q-Learning for Partially Observable MDPs Matthew Hausknecht and Peter Stone University of Texas at Austin November 13, 2015 1 Motivation Intelligent decision making is the heart of AI 2 Motivation Intelligent decision making

808 views • 52 slides
Virtual Memory Paging An important task of a virtual-memory system is to relocate pages from

Virtual Memory Paging An important task of a virtual-memory system is to relocate pages from

Virtual Memory Paging An important task of a virtual-memory system is to relocate pages from physical memory out to disk Early UNIX systems swapped out the entire process at once Modern UNIX systems relay more on paging In

434 views • 15 slides
Recurrent Neural Networks Greg Mori - CMPT 419/726 Goodfellow, Bengio, and Courville: Deep

Recurrent Neural Networks Greg Mori - CMPT 419/726 Goodfellow, Bengio, and Courville: Deep

Recurrent Neural Networks Long Short-Term Memory Temporal Convolutional Networks Examples Recurrent Neural Networks Greg Mori - CMPT 419/726 Goodfellow, Bengio, and Courville: Deep Learning textbook Ch. 10 Recurrent Neural Networks Long

667 views • 18 slides
Memory networks Zhirong Wu Feb 9th, 2015 Outline motivation Most machine learning algorithms

Memory networks Zhirong Wu Feb 9th, 2015 Outline motivation Most machine learning algorithms

Memory networks Zhirong Wu Feb 9th, 2015 Outline motivation Most machine learning algorithms try to learn a static mapping, and it has been elusive to incorporate memory in the learning. Despite its wide-ranging success in modelling

845 views • 37 slides
Expanding t the W World o of H Heterogenous Mem emory H y Hier erarchies The Evolving

Expanding t the W World o of H Heterogenous Mem emory H y Hier erarchies The Evolving

Expanding t the W World o of H Heterogenous Mem emory H y Hier erarchies The Evolving Non-Volatile Memory Story Bill Gervasi Principal Systems Architect 16 May 2019 2 Data Memory Checkpointing Processing Tiers Challenges

1.69k views • 119 slides

More recommend