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Data Microsoft Office

Location:
Noblesville, IN
Posted:
November 13, 2018

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Resume:

Yan Peng

***** ****** **., ******* ******* ***** ac7osj@r.postjobfree.com 813-***-****

Summary

• With strong understanding of data structures, data science, web development and algorithms, seeking a challenging internship/fulltime position in the field of Computer Science and Software Engineering.

Education

• Purdue University

Bachelor of Science in Computer Science, Minor in Mathematics Indiana,USA

Aug. 2013 – May. 2018

Skills

• Programming Language: Java, C/C++, Python, HTML5/JavaScript/Ajax/CSS, R PHP, D3, Objective C

• Software: Git/GitHub, Eclipse, Virtual Machine, Visual Studio, Microsoft Office, MySQL, Google Cloud, Android Studio, Rstudio, NumPy, Scikit-learn, Tensorflow

• System Enviornment: Linux, MacOs, Windows

• Foreign Language: Mandarin and Cantonese

• Passed Computer Science Major field test

Projects

Capstone Project: Smart home system prototype

Internet of Thing application which requires both back-end and front-end using Contiki-Operating System using C language and Python

• Built an enviornment monitoring system with some on-board sensor built on the commodity hardware (TelosB)

• Built a Python server on Serial port using RPL packets and connect the smart home system to PC

• Built an ADC driver to connect external sensor with commodity hardware

• Built UDP client and UDP server to do data collection and store data into database, also send notifications when sensor reading exceeds some threshold

Online Shopping system

Web application of an Online Shopping System

• Developed an interactive web page

• Developed a web service using PHP

• Utilized MySQL to store product information

• Implemented a content-based online shopping algorithm Parole Recognition System

Data Science web application system, use big data of images to do prediction. Use

• Acquire a big database of faces and split: “parole” & “not parole” for back-end

• Randomly assign each data point to either a test, train or validation group with different model.

• Train data with a transfer learning and auto-encoder and discern different features

• For front-end interface will be a web application that retrieves images through database and send the data to a bac-kend Python program with a “yes” or “no” in return.



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