13 Ekim 2015 saat 19:00’da Hacettepe Teknokent Safir Bloklar Konferans Salonunda gerçekleştirdiğimiz Derin Öğrenme etkinliğinin video ve sunum dosyasına aşağıdan erişebilirsiniz.
derin_ogrenme_linked_13.10.2015.pdf
A neural network is an artificial intelligence technique that is based on biological synapses and neurons. Neural networks can be used to solve difficult or impossible problems such as predicting which team will win the Super Bowl or whether a company’s stock price will go up or down. In a short and informal session, Dr. James McCaffrey, from Microsoft Research in Redmond, WA, will describe exactly what neural networks are, explain the types of problems that can be solved using neural networks, and demonstrate how to create neural networks from scratch using Visual Studio. You will leave this session with an in-depth understanding of neural networks and get some early information about a related, soon-to-be-released Microsoft product.
Derin Öğrenme Yaz Okulu Montreal/Kanada’da Ağustos 2015 ayında icra edildi. 10 günlük faaliyette derin öğrenmenin kullanım alanlarına yönelik konusunda uzman kişilerin katıldığı sunumlar ve otonom sistem demoları yapıldı. Aşağıda günlük programlar halinde sunulan sunumları indirip inceleyebilirsiniz.
| 1’inci Gün – 03 Ağustos 2015 |
|---|
| Pascal Vincent: Intro to ML |
| Yoshua Bengio: Theoretical motivations for Representation Learning & Deep Learning |
| Leon Bottou: Intro to multi-layer nets |
| 2’nci Gün – 04 Ağustos 2015 |
|---|
| Hugo Larochelle: Neural nets and backprop |
| Leon Bottou: Numerical optimization and SGD, Structured problems & reasoning |
| Hugo Larochelle: Directed Graphical Models and NADE |
| Intro to Theano |
| 3’üncü Gün – 05 Ağustos 2015 |
|---|
| Aaron Courville: Intro to undirected graphical models |
| Honglak Lee: Stacks of RBMs |
| Pascal Vincent: Denoising and contractive auto-encoders, manifold view |
| 4’üncü Gün – 06 Ağustos 2015 |
|---|
| Roland Memisevic: Visual features |
| Honglak Lee: Convolutional networks |
| Graham Taylor: Learning similarit |
| 5’inci Gün – 07 Ağustos 2015 |
|---|
| Chris Manning: NLP 101 |
| Graham Taylor: Modeling human motion, pose estimation and tracking |
| Chris Manning: NLP / Deep Learning |
| 6’ncı Gün – 08 Ağustos 2015 |
|---|
| Ruslan Salakhutdinov: Deep Boltzmann Machines |
| Adam Coates: Speech recognition with deep learning |
| Ruslan Salakhutdinov: Multi-modal models |
| 7’nci Gün – 09 Ağustos 2015 |
|---|
| Ian Goodfellow: Structure of optimization problems |
| Adam Coates: Systems issues and distributed training |
| Ian Goodfellow: Adversarial examples |
| 8’inci Gün – 10 Ağustos 2015 |
|---|
| Phil Blunsom: From language modeling to machine translation |
| Richard Socher: Recurrent neural networks |
| Phil Blunsom: Memory, Reading, and Comprehension |
| 9’uncu Gün – 11 Ağustos 2015 |
|---|
| Richard Socher: DMN for NLP |
| Mark Schmidt: Smooth, Finite, and Convex Optimization |
| Roland Memisevic: Visual Features II |
| 10’uncu Gün – 12 Ağustos 2015 |
|---|
| Mark Schmidt: Non-Smooth, Non-Finite, and Non-Convex Optimization |
| Aaron Courville: VAEs and deep generative models for vision |
| Yoshua Bengio: Generative models from auto-encoder |
Tüm sunumları indirmek için tıklayınız.
Kaynaklar: