Pinned Repositories
amandReadMe
Amendment of ReadMe file in Pristine template
amendPristineCLIReadMe
Amendment of Pristine CLI ReadMe file.
datax
Data-X
fa19
Public repository for course content and ds100.org/fa19.
loan_eligibility_web_app_project_1
Onboarding-Project-Leica-M
Webpage created for ETC Labs' onboarding challenge.
Pristine-Trial
This is a trial for Pristine.
Questions-of-Pristine
Some questions I have
Spam-Ham-E-mail
By exploring datasets composed of thousands of e-mails and engineering the features, I was able to select out the best features and build a model to determine whether or not the e-mail tested is spam or not. The test accuracy is 91%.
spam-ham-email
By exploring datasets composed of thousands of e-mails and engineering the features, I was able to select out the best features and build a model to determine whether or not the e-mail tested is spam or not. The test accuracy is 91%.
JiangHaoliangUCB's Repositories
JiangHaoliangUCB/amandReadMe
Amendment of ReadMe file in Pristine template
JiangHaoliangUCB/amendPristineCLIReadMe
Amendment of Pristine CLI ReadMe file.
JiangHaoliangUCB/datax
Data-X
JiangHaoliangUCB/fa19
Public repository for course content and ds100.org/fa19.
JiangHaoliangUCB/loan_eligibility_web_app_project_1
JiangHaoliangUCB/Onboarding-Project-Leica-M
Webpage created for ETC Labs' onboarding challenge.
JiangHaoliangUCB/Pristine-Trial
This is a trial for Pristine.
JiangHaoliangUCB/Questions-of-Pristine
Some questions I have
JiangHaoliangUCB/Spam-Ham-E-mail
By exploring datasets composed of thousands of e-mails and engineering the features, I was able to select out the best features and build a model to determine whether or not the e-mail tested is spam or not. The test accuracy is 91%.
JiangHaoliangUCB/spam-ham-email
By exploring datasets composed of thousands of e-mails and engineering the features, I was able to select out the best features and build a model to determine whether or not the e-mail tested is spam or not. The test accuracy is 91%.
JiangHaoliangUCB/spam-or-ham
By exploring datasets composed of thousands of e-mails and engineering the features, I was able to select out the best features and build a model to determine whether or not the e-mail tested is spam or not. The test accuracy is 91%.
JiangHaoliangUCB/spy500-tail-analysis
Using power law to fit and model the abnormal stock prices in the tail of the distribution of SPY 500 prices.