cs230.stanford.edu · The dataset was obtained through the Kern Scores library at the Center...

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Transcript of cs230.stanford.edu · The dataset was obtained through the Kern Scores library at the Center...

Page 1: cs230.stanford.edu · The dataset was obtained through the Kern Scores library at the Center Computer Assisted Research in the Humanities at Stanford University[l()]. Kern contains
Page 2: cs230.stanford.edu · The dataset was obtained through the Kern Scores library at the Center Computer Assisted Research in the Humanities at Stanford University[l()]. Kern contains
Page 3: cs230.stanford.edu · The dataset was obtained through the Kern Scores library at the Center Computer Assisted Research in the Humanities at Stanford University[l()]. Kern contains
Page 4: cs230.stanford.edu · The dataset was obtained through the Kern Scores library at the Center Computer Assisted Research in the Humanities at Stanford University[l()]. Kern contains
Page 5: cs230.stanford.edu · The dataset was obtained through the Kern Scores library at the Center Computer Assisted Research in the Humanities at Stanford University[l()]. Kern contains
Page 6: cs230.stanford.edu · The dataset was obtained through the Kern Scores library at the Center Computer Assisted Research in the Humanities at Stanford University[l()]. Kern contains

cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8290434.pdf · A Content-Based Image Retrieval System (CBIR) for eCommerce Purposes Using Deep Neural Networks Lee

cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8290434.pdf · A Content-Based Image Retrieval System (CBIR) for eCommerce Purposes Using Deep Neural Networks Lee

cs230.stanford.educs230.stanford.edu › projects_winter_2019 › posters › 15794817.pdf · on the signal of similar pixels2. Here we use the scikit-image fast-mode implementation

cs230.stanford.educs230.stanford.edu › projects_winter_2019 › posters › 15794817.pdf · on the signal of similar pixels2. Here we use the scikit-image fast-mode implementation

Generating Probability Distributions for Future Stock …cs230.stanford.edu/projects_winter_2020/reports/32144605.pdfGenerating Probability Distributions for Future Stock Prices Jeffrey

Generating Probability Distributions for Future Stock …cs230.stanford.edu/projects_winter_2020/reports/32144605.pdfGenerating Probability Distributions for Future Stock Prices Jeffrey

Midterm Review - CS230 Deep Learningcs230.stanford.edu/fall2018/midterm_review.pdf · Midterm Review CS230 Fall 2018. Broadcasting. Calculating Means How would you calculate the means

Midterm Review - CS230 Deep Learningcs230.stanford.edu/fall2018/midterm_review.pdf · Midterm Review CS230 Fall 2018. Broadcasting. Calculating Means How would you calculate the means

CS230: Lecture 9 Deep Reinforcement Learningcs230.stanford.edu/spring2020/lecture9.pdfCS230: Lecture 9 Deep Reinforcement Learning Kian Katanforoosh Kian Katanforoosh I. Motivation

CS230: Lecture 9 Deep Reinforcement Learningcs230.stanford.edu/spring2020/lecture9.pdfCS230: Lecture 9 Deep Reinforcement Learning Kian Katanforoosh Kian Katanforoosh I. Motivation

CS230: Lecture 3cs230.stanford.edu/files/lecture-notes-3.pdf · CS230: Lecture 3 The mathematics of deep learning Backpropagation, Initializations, Regularization Kian Katanforoosh.

CS230: Lecture 3cs230.stanford.edu/files/lecture-notes-3.pdf · CS230: Lecture 3 The mathematics of deep learning Backpropagation, Initializations, Regularization Kian Katanforoosh.

CS230-Fall 2019 Final Project Report Painting Genre ...cs230.stanford.edu/projects_fall_2019/reports/26180781.pdf · CS230-Fall 2019 Final Project Report Painting Genre Classification

CS230-Fall 2019 Final Project Report Painting Genre ...cs230.stanford.edu/projects_fall_2019/reports/26180781.pdf · CS230-Fall 2019 Final Project Report Painting Genre Classification

CS230: Lecture 5cs230.stanford.edu/fall2017/files/CS230_Handout6.pdf · CS230: Lecture 5 Advanced topics in Object Detection Kian Katanforoosh, Andrew Ng Stanford University. Kian

CS230: Lecture 5cs230.stanford.edu/fall2017/files/CS230_Handout6.pdf · CS230: Lecture 5 Advanced topics in Object Detection Kian Katanforoosh, Andrew Ng Stanford University. Kian

CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8290634.pdf · alternative of rating food photos' attractiveness to Yelp's published approach that utilized EXIF

CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8290634.pdf · alternative of rating food photos' attractiveness to Yelp's published approach that utilized EXIF

cs230.stanford.educs230.stanford.edu/projects_spring_2019/reports/18681618.pdf · Tool detection:Used Fast-RCNN for spatial detection of surgical tools and VGG16 for classification

cs230.stanford.educs230.stanford.edu/projects_spring_2019/reports/18681618.pdf · Tool detection:Used Fast-RCNN for spatial detection of surgical tools and VGG16 for classification

cs230.stanford.educs230.stanford.edu/projects_spring_2019/reports/18680300.pdfThe following equation gives the final probability density function (pdf) to predict the network output

cs230.stanford.educs230.stanford.edu/projects_spring_2019/reports/18680300.pdfThe following equation gives the final probability density function (pdf) to predict the network output

Real-Time Seismic Attributes Computation with Conditional …cs230.stanford.edu/projects_winter_2020/reports/32623969.pdfIn this context, seismic attributes contribute to the process,

Real-Time Seismic Attributes Computation with Conditional …cs230.stanford.edu/projects_winter_2020/reports/32623969.pdfIn this context, seismic attributes contribute to the process,

cs230.stanford.edu · making geologically reasonable and consistent predictions for seismic facies. 1 Introduction The increasing availability of three-dimensional (3D) seismic data

cs230.stanford.edu · making geologically reasonable and consistent predictions for seismic facies. 1 Introduction The increasing availability of three-dimensional (3D) seismic data

cs230.stanford.educs230.stanford.edu/files_winter_2018/projects/6940224.pdf · Exploring Knowledge Distillation of Deep Neural Networks for Efficient Hardware Solutions Haitong Li

cs230.stanford.educs230.stanford.edu/files_winter_2018/projects/6940224.pdf · Exploring Knowledge Distillation of Deep Neural Networks for Efficient Hardware Solutions Haitong Li

CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15806293.pdf · Most sentiment analysis studies in the finance and accounting literature use ... Apple Inc. : ]

CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15806293.pdf · Most sentiment analysis studies in the finance and accounting literature use ... Apple Inc. : ]

cs230.stanford.educs230.stanford.edu/projects_fall_2018/posters/12377987.pdf · U.S. Timely, accurate diagnosis is a critical factor in determining patient outcomes. Currently, pneumonia

cs230.stanford.educs230.stanford.edu/projects_fall_2018/posters/12377987.pdf · U.S. Timely, accurate diagnosis is a critical factor in determining patient outcomes. Currently, pneumonia

cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8291220.pdf · Much of the published research on applying DL techniques in financial market applications is based

cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8291220.pdf · Much of the published research on applying DL techniques in financial market applications is based

CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15813380.pdf · CS230 Final Project: Milestone Topic: Transfer Learning Ajay Sohmshetty (collaboration with Amir

CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15813380.pdf · CS230 Final Project: Milestone Topic: Transfer Learning Ajay Sohmshetty (collaboration with Amir

CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15782825.pdf · Generative Adversarial Networks (GANs) [Goodfellow et al, 2014; Isola et al, 2017] and Variational

CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15782825.pdf · Generative Adversarial Networks (GANs) [Goodfellow et al, 2014; Isola et al, 2017] and Variational

CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8289231.pdf · high gesture classification accuracy can be achieved using a convolutional neural network trained

CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8289231.pdf · high gesture classification accuracy can be achieved using a convolutional neural network trained