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CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/posters/8284325.pdf · 2018. 9. 28. · Aditya Chander ( [email protected] ), Marina Cottrell ( [email protected] ),

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Page 1: CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/posters/8284325.pdf · 2018. 9. 28. · Aditya Chander ( ac888@stanford.edu ), Marina Cottrell ( mborsodi@stanford.edu ),

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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Healthcare DL for - Deep Learningcs230.stanford.edu/files/Deep Learning in Healthcare.pdf · Future of diagnostic access 1. Improve healthcare delivery. CheXNet can help radiologists

Healthcare DL for - Deep Learningcs230.stanford.edu/files/Deep Learning in Healthcare.pdf · Future of diagnostic access 1. Improve healthcare delivery. CheXNet can help radiologists

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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 Deep Learningcs230.stanford.edu/projects_spring_2018/posters/8285188.pdfExplore and develop a deep machine learning model that predicts the future price of digital asset such

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

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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

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CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15812441.pdfStackGAN managed to generate more realistic, higher resolution images by splitting the problem into two

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Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8291012.pdfFor the 2D CNN and RNN models, the spectrogram of the time-series data is used . as input (spectrogram is a

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CS230 Deep Learningcs230.stanford.edu/files_winter_2018/projects/6940506.pdf · OCR focused on historical transcription has been rarely applied on Arabic historical manuscripts

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Bankruptcy Prediction by Deep Learningcs230.stanford.edu/projects_winter_2020/reports/32569269.pdf · Deep learning techniques, as the Convolutional Neural Networks (CNN) have only

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CS230 Deep Learningcs230.stanford.edu/files_winter_2018/projects/6940460.pdf · also begun exploring deep unsupervised learning methods in the healthcare setting. One example includes

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CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15808904.pdf · Erick Cardenas implemented the Convolutional Baseline model, setup and managed the AWS instances

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CS230 Deep Learningcs230.stanford.edu/projects_spring_2018/reports/8290329.pdf · 2018-09-28 · Medical diagnostics with retinal images is an active area of research in the deep-

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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

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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

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CS230 Deep Learningcs230.stanford.edu/projects_winter_2019/reports/15871106.pdf5.0.2 Models Using the retrained Inception ResNet classifier, we ran several experiments to test the

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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

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CS230 Deep Learningcs230.stanford.edu/projects_spring_2019/reports/18678885.pdfis a treasure trove of information, including that related to virality, user sentiment, networks, and

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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

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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

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cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8270111.pdf · With our efforts through this quarter, we have successfully built a speaker identification algorithm

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cs230.stanford.educs230.stanford.edu/projects_spring_2018/reports/8288669.pdf · Hiro Tien (Kai Ping) Stanford Graduate School of Business Stanford School of Earth, Energy & Environmental

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