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Page 1: Discussion & Future Work Models for Willingness Problem …cs229.stanford.edu/proj2018/poster/120.pdf · 2019. 1. 6. · 1. Logistic Regression (binary configuration with L 2 regu-

Airbnb Price Estimation CS 229: Machine Learning Liubov …cs229.stanford.edu/proj2018/poster/96.pdf · • Results: Using feature selection, hyperparameter tuning, and a variety

HITPREDICT: PREDICTING HIT SONGS USING SPOTIFY DATA …cs229.stanford.edu/proj2018/report/16.pdf · 2019-01-06 · (hits) and negative (non-hits) examples, we removed two thirds of

Fine-Grained Sentiment Analysis of Restaurant Customer …cs229.stanford.edu/proj2018/report/195.pdf · 2019-01-06 · Recent years have seen a substantial progress in NLP tasks with

Abstract - cs229.stanford.edu

MachineLearning CS229/STATS229

Convolutional Neural Network Approach CS 229 Machine ...cs229.stanford.edu/proj2018/poster/58.pdf · the imagehas been resized in 256 x 256 x 3 using the cv2 packagein python. Table

CS229 FINAL PROJECT 1 Reduced order modeling approach for cardiovascular stent …cs229.stanford.edu/proj2016/report/ROMberkin.pdf · 2017-09-23 · CS229 FINAL PROJECT 1 Reduced

Reconstructing Pore Networks Using Generative Adversarial ...cs229.stanford.edu/proj2018/report/222.pdfto capture an adequate area, the image was downsampled to 2563 voxels with a

A “generative” model for computing electromagnetic ﬁeld …cs229.stanford.edu/proj2018/report/233.pdfA “generative” model for computing electromagnetic ﬁeld solutions Ben

Using Latent Embeddings of Wikipedia Articles to Predict ...cs229.stanford.edu/proj2018/poster/134.pdf · Using Latent Embeddings of Wikipedia Articles to Predict Poverty Evan Sheehan,

CS229 PROJECT REPORT - GitHub Pages

CS229: Machine Learning

CS 229 Project Final Report A Method for Modifying Facial ...cs229.stanford.edu/proj2018/report/42.pdf · when faces are intelligently selected from the images. Cropping out faces

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Satellite-Based Prediction of Fire Risk in Northern ...cs229.stanford.edu/proj2018/report/210.pdf · Final Report: Fire Risk Prediction Famiglietti, Holtzman, & Campolo described

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cs229.stanford.educs229.stanford.edu/proj2018/poster/159.pdf · Title: poster229 (Deng Yong's conflicted copy 2018-12-09) (Deng Yong's conflicted copy 2018-12-09) Created Date: 12/10/2018

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CS229 Final Project: Language Grounding in Minecraft with ...cs229.stanford.edu/proj2017/final-reports/5242630.pdf · CS229 Final Project: Language Grounding in Minecraft with Gated-Attention

Lasso Regression - cs229.stanford.edu

Residential Electric Vehicle Charging Characterization via …cs229.stanford.edu/proj2018/report/221.pdf · 2019-03-03 · Residential Electric Vehicle Charging Characterization via

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PCA outperforms MethylMix algorithm Early Stage …cs229.stanford.edu/proj2018/poster/148.pdf“MethylMix 2.0: an R package for identifying DNA methylation genes,” Bioinformatics,

CS229 - Probability Theory Review

Isolating single cell types from co-culture flow cytometry …cs229.stanford.edu/proj2018/report/144.pdf · 2019. 1. 6. · Isolating single cell types from co-culture flow cytometry

CS229 MACHINE LEARNING, STANFORD UNIVERSITY, …cs229.stanford.edu/proj2016/report/FegelisHebert...CS229 MACHINE LEARNING, STANFORD UNIVERSITY, DECEMBER 2016 3 t= f(k x t +h y t) (6)

doodles Input (28x28x1) Models produced scores that were ...cs229.stanford.edu/proj2018/poster/98.pdf · Quick, Draw! Doodle Recognition Kristine Guo ([email protected]), James

m for various of semantic relationships Overview Models …cs229.stanford.edu/proj2018/poster/203.pdf · 2019-01-06 · t-Distributed Stochastic Neighbor Embedding (t-SNE) for constructing

How Real is Real? Quantitative and Qualitative comparison ...cs229.stanford.edu/proj2018/report/102.pdfThe fully connected NN takes in the input image with di-mensions 1 x 28 x 28,

boosting - cs229.stanford.edu

,.~R REGU(.q;. . 0 - NRC