|
gptkbp:instanceOf
|
gptkb:university
|
|
gptkbp:course
|
gptkb:CS231n
|
|
gptkbp:department
|
gptkb:Stanford_Computer_Science_Department
|
|
gptkbp:firstTaught
|
2015
|
|
gptkbp:focusesOn
|
computer vision
convolutional neural networks
deep learning
|
|
gptkbp:fullName
|
gptkb:Convolutional_Neural_Networks_for_Visual_Recognition
|
|
gptkbp:grades
|
assignments and project
|
|
gptkbp:hasAssignments
|
yes
|
|
gptkbp:hasFinalExam
|
no
|
|
gptkbp:hasLectureVideos
|
yes
|
|
gptkbp:hasMidterm
|
no
|
|
gptkbp:hasSyllabus
|
yes
|
|
gptkbp:hasTextbook
|
no official textbook
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
CS231n
|
|
gptkbp:instructors
|
gptkb:Serena_Yeung
gptkb:Andrej_Karpathy
gptkb:Fei-Fei_Li
gptkb:Justin_Johnson
|
|
gptkbp:languageOfInstruction
|
English
|
|
gptkbp:level
|
graduate
advanced undergraduate
|
|
gptkbp:location
|
gptkb:Stanford,_California
|
|
gptkbp:materialsAvailableOnline
|
yes
|
|
gptkbp:notableAlumni
|
gptkb:Andrej_Karpathy
students who became AI researchers
|
|
gptkbp:notableFor
|
influential in deep learning education
popular YouTube lectures
widely used lecture materials
|
|
gptkbp:notableProject
|
yes
|
|
gptkbp:offeredBy
|
gptkb:Stanford_University
|
|
gptkbp:openToPublic
|
yes
|
|
gptkbp:prerequisite
|
probability
linear algebra
Python programming
machine learning basics
|
|
gptkbp:semesterOffered
|
gptkb:spring
|
|
gptkbp:topic
|
optimization
generative models
recurrent neural networks
transfer learning
image classification
object detection
visual recognition
neural network architectures
visualizing and understanding CNNs
|
|
gptkbp:usesFrameworks
|
gptkb:TensorFlow
gptkb:PyTorch
|
|
gptkbp:website
|
http://cs231n.stanford.edu/
|
|
gptkbp:bfsParent
|
gptkb:Andrej_Karpathy
|
|
gptkbp:bfsLayer
|
7
|