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web.stanford.eduweb.stanford.edu/class/cs230/projects_spring_2018/... · Medical diagnostics with retinal images is an active area of research in the deep- learning community. Building

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Page 1: web.stanford.eduweb.stanford.edu/class/cs230/projects_spring_2018/... · Medical diagnostics with retinal images is an active area of research in the deep- learning community. Building
Page 2: web.stanford.eduweb.stanford.edu/class/cs230/projects_spring_2018/... · Medical diagnostics with retinal images is an active area of research in the deep- learning community. Building
Page 3: web.stanford.eduweb.stanford.edu/class/cs230/projects_spring_2018/... · Medical diagnostics with retinal images is an active area of research in the deep- learning community. Building
Page 4: web.stanford.eduweb.stanford.edu/class/cs230/projects_spring_2018/... · Medical diagnostics with retinal images is an active area of research in the deep- learning community. Building
Page 5: web.stanford.eduweb.stanford.edu/class/cs230/projects_spring_2018/... · Medical diagnostics with retinal images is an active area of research in the deep- learning community. Building
Page 6: web.stanford.eduweb.stanford.edu/class/cs230/projects_spring_2018/... · Medical diagnostics with retinal images is an active area of research in the deep- learning community. Building

cs230.stanford.educs230.stanford.edu/projects_spring_2018/posters/8285590.pdf · melody. Chord arrangement involves both conventional rules and creativity. Ideal model: Generate chords

cs230.stanford.educs230.stanford.edu/projects_spring_2018/posters/8285590.pdf · melody. Chord arrangement involves both conventional rules and creativity. Ideal model: Generate chords

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CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8289986.pdfBossard, Guillaumin and Gool, in 2014, created the Food-101 dataset [1], one of the first detailed, high

CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8289986.pdfBossard, Guillaumin and Gool, in 2014, created the Food-101 dataset [1], one of the first detailed, high

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CS230: Lecture 3 · CS230: Lecture 3 The mathematics of deep learning Backpropagation, Initializations, Regularization Kian Katanforoosh

CS230: Lecture 3 · CS230: Lecture 3 The mathematics of deep learning Backpropagation, Initializations, Regularization Kian Katanforoosh

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cs230.stanford.educs230.stanford.edu/projects_spring_2018/posters/8285130.pdf · Image Restoration of Noisy and Low-Quality Retinal Images Katherine Sytwul, Fariah Hayee2 Dept. of

cs230.stanford.educs230.stanford.edu/projects_spring_2018/posters/8285130.pdf · Image Restoration of Noisy and Low-Quality Retinal Images Katherine Sytwul, Fariah Hayee2 Dept. of

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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

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CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/posters/8290961.pdf · Image Selection Criteria: Using demo code from the B-IT-BOTS teaml, we can select images that contain

CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/posters/8290961.pdf · Image Selection Criteria: Using demo code from the B-IT-BOTS teaml, we can select images that contain

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web.stanford.eduweb.stanford.edu/class/cs230/files_winter_2018/projects/6939387.pdf · product (e.g. women's jumpsuits). We collected the images by scraping seven shopping sites I

web.stanford.eduweb.stanford.edu/class/cs230/files_winter_2018/projects/6939387.pdf · product (e.g. women's jumpsuits). We collected the images by scraping seven shopping sites I

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PROGRAM 1 CITIZEN FSKM MAC 2013 23/3 - … €siti rabiah binti mahadi€ €cs230€ a4 65 €siti rokiah binti mahadi€ €cs230€ a3 66 €siti roslina binti roslim€ €cs230€

PROGRAM 1 CITIZEN FSKM MAC 2013 23/3 - … €siti rabiah binti mahadi€ €cs230€ a4 65 €siti rokiah binti mahadi€ €cs230€ a3 66 €siti roslina binti roslim€ €cs230€

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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

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CS230: Lecture 5 Case Study

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cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8284387.pdf · 2018-09-28 · these phrases are consistent with the English language, the output does not represent

cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8284387.pdf · 2018-09-28 · these phrases are consistent with the English language, the output does not represent

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CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8271110.pdf · 2018. 9. 28. · reconstruction using e.g. template fitting. None of these methods are fully satisfactory

CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8271110.pdf · 2018. 9. 28. · reconstruction using e.g. template fitting. None of these methods are fully satisfactory

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CS230: Lecture 9 Deep Reinforcement Learning

CS230: Lecture 9 Deep Reinforcement Learning

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cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8289614.pdfduration, or only textual features, such as project description and keywords. To our knowledge, we are

cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8289614.pdfduration, or only textual features, such as project description and keywords. To our knowledge, we are

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web.stanford.eduweb.stanford.edu/class/cs230/projects_spring_2018/... · 50 image as input, and generate a higher resolution 250 x 250 output image. 2. Related Work This project was

web.stanford.eduweb.stanford.edu/class/cs230/projects_spring_2018/... · 50 image as input, and generate a higher resolution 250 x 250 output image. 2. Related Work This project was

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CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8285485.pdf · For our project we use the following data set the "Coupon Purchase Prediction" challenge from the

CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8285485.pdf · For our project we use the following data set the "Coupon Purchase Prediction" challenge from the

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

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CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8289721.pdf · Solar energy has become a vital part of the energy infrastructure and ... copy and crop max pool

CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8289721.pdf · Solar energy has become a vital part of the energy infrastructure and ... copy and crop max pool

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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

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web.stanford.eduweb.stanford.edu/~kiparsky/Papers/WordFormationMALC1982.pdf · web.stanford.edu

web.stanford.eduweb.stanford.edu/~kiparsky/Papers/WordFormationMALC1982.pdf · web.stanford.edu

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Stanford Universityweb.stanford.edu/class/cs230/projects_spring_2018/... · 2018-09-28 · News Article Prediction Using Deep Learning Research conducted in CS230: Deep Learning at

Stanford Universityweb.stanford.edu/class/cs230/projects_spring_2018/... · 2018-09-28 · News Article Prediction Using Deep Learning Research conducted in CS230: Deep Learning at

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CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8290890.pdfFigure 1: Next Pitch Type Prediction Problem Unlike other sports, a baseball game can be described well

CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8290890.pdfFigure 1: Next Pitch Type Prediction Problem Unlike other sports, a baseball game can be described well

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cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8288946.pdf · jazz piano piece). It was converted into a text file, which contains its noteOn, noteOff, control

cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8288946.pdf · jazz piano piece). It was converted into a text file, which contains its noteOn, noteOff, control

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CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8291200.pdf · 2018. 9. 28. · Given the amount of data we have, we used an 80/10/10 split, with 80 percent of

CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8291200.pdf · 2018. 9. 28. · Given the amount of data we have, we used an 80/10/10 split, with 80 percent of

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cs230.stanford.educs230.stanford.edu/projects_winter_2019/reports/15813002.pdf · global education equity (4). CS230: Deep Learning, Winter 2019, Stanford ... To evolve beyond our

cs230.stanford.educs230.stanford.edu/projects_winter_2019/reports/15813002.pdf · global education equity (4). CS230: Deep Learning, Winter 2019, Stanford ... To evolve beyond our

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CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8290433.pdf · Stanford University {zhaozhuo, zhiyuan8, edu Abstract Damage of building is an essential indicator

CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8290433.pdf · Stanford University {zhaozhuo, zhiyuan8, edu Abstract Damage of building is an essential indicator

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CS230 Deep Learning › projects_spring_2018 › reports › 8291206.pdf · I used NLKT's [8] PUNK T Word Tokenizer to split the headlines into words. Examining the data manually,

CS230 Deep Learning › projects_spring_2018 › reports › 8291206.pdf · I used NLKT's [8] PUNK T Word Tokenizer to split the headlines into words. Examining the data manually,

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CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8316972.pdf · deep learning based methodology to learn a similarity mea- sure between street and shop photos. 2

CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8316972.pdf · deep learning based methodology to learn a similarity mea- sure between street and shop photos. 2

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web.stanford.eduweb.stanford.edu/class/ips216/Readings/galtung_67.pdf · web.stanford.edu

web.stanford.eduweb.stanford.edu/class/ips216/Readings/galtung_67.pdf · web.stanford.edu

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cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8289547.pdf · MOOCs and online courses have notoriously high attrition [1]. One challenge is ... a student's performance

cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8289547.pdf · MOOCs and online courses have notoriously high attrition [1]. One challenge is ... a student's performance

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