• Introduction of this course: pdf,pptx (2017/02/23)
  • Regression: pdf,pptx,video (2017/03/02)
  • Where does the error come from?: pdf,pptx,video (2017/03/02, recorded at 2016/10/07)
  • Gradient Descent: pdf,pptx,video (2017/03/09, recorded at 2016/10/07)
  • Classification: Probabilistic Generative Model pdf, pptx, video (2017/03/16, recorded at 2016/10/07)
  • Classification: Logistic Regression pdf, pptx, video (2017/03/23, part of the video recorded at 2016/10/14)
  • Introduction of Deep Learning pdf, pptx, video (2017/03/23, recorded at 2016/10/14)
  • Backpropagation pdf, pptx, video (2017/03/23)
  • “Hello world” of Deep Learning pdf, pptx, video (2017/03/23)
  • Tips for Deep Learning pdf, pptx, video (2017/03/30)
  • Convolutional Neural Network pdf, pptx, video (2017/04/06)
  • Why Deep? pdf, pptx, video (2017/04/06, recorded at 2016/11/04)
  • Semi-supervised Learning pdf, pptx, video (2017/04/13, recorded at 2016/11/11)
  • Unsupervised Learning: Principle Component Analysis pdf, pptx, video (2017/04/13, recorded at 2016/11/11)
  • Unsupervised Learning: Neighbor Embedding pdf, pptx, video (2017/04/20)
  • Unsupervised Learning: Deep Auto-encoder pdf, pptx, video (2017/04/20)
  • Unsupervised Learning: Word Embedding pdf, pptx, video (2017/04/27)
  • Unsupervised Learning: Deep Generative Model pdf, pptx, video (2017/04/27)
  • Transfer Learning pdf, pptx, video (2017/05/03)
  • Recurrent Neural Network pdf, pptx, video (part 1), video (part 2) (recorded at 2016/12/30)
  • Matrix Factorization pdf, pptx, video (2017/05/25)
  • Ensemble pdf, pptx, video (2017/05/25)
  • Introduction of Structured Learning pdf, pptx, video (part 1), video (part 1) (2017/06/01)
  • Introduction of Reinforcement Learning pdf, pptx, video (2017/06/15)