CS231n Winter 2016: Lecture 2: Data-driven approach, kNN, Linear Classification 1

Lecture 2 of 15 in Computer Vision (Stanford CS231n) by Andrej Karpathy. 57 min. Watch on YouTube

Course: Computer Vision (Stanford CS231n) (Computer Science). Covers: computer vision convolutional neural networks cnn image classification detection.

All lectures in Computer Vision (Stanford CS231n)

  1. CS231n Winter 2016: Lecture1: Introduction and Historical Context · 1 h 19 min
  2. CS231n Winter 2016: Lecture 2: Data-driven approach, kNN, Linear Classification 1 · 57 min
  3. CS231n Winter 2016: Lecture 3: Linear Classification 2, Optimization · 1 h 11 min
  4. CS231n Winter 2016: Lecture 4: Backpropagation, Neural Networks 1 · 1 h 20 min
  5. CS231n Winter 2016: Lecture 5: Neural Networks Part 2 · 1 h 19 min
  6. CS231n Winter 2016: Lecture 6: Neural Networks Part 3 / Intro to ConvNets · 1 h 10 min
  7. CS231n Winter 2016: Lecture 7: Convolutional Neural Networks · 1 h 19 min
  8. CS231n Winter 2016: Lecture 8: Localization and Detection · 1 h 5 min
  9. CS231n Winter 2016: Lecture 9: Visualization, Deep Dream, Neural Style, Adversarial Examples · 1 h 18 min
  10. CS231n Winter 2016: Lecture 10: Recurrent Neural Networks, Image Captioning, LSTM · 1 h 10 min
  11. CS231n Winter 2016: Lecture 11: ConvNets in practice · 1 h 15 min
  12. CS231n Winter 2016: Lecture 12: Deep Learning libraries · 1 h 21 min
  13. CS231n Winter 2016: Lecture 13: Segmentation, soft attention, spatial transformers · 1 h 11 min
  14. CS231n Winter 2016: Lecture 14: Videos and Unsupervised Learning · 1 h 18 min
  15. CS231n Winter 2016: Lecture 15: Invited Talk by Jeff Dean · 1 h 15 min