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Candidate's Name
PHONE NUMBER AVAILABLE
EMAIL AVAILABLE Candidate's Name -Street Address
Jaymin1612
SUMMARY
Passionate and enthusiastic about data to extract information from it and develop models using different machine learning techniques.
EDUCATION
MACHINE LEARNING NANODEGREE - UDACITY
PROJECTS: Titanic survivors, Boston housing price, Finding Donors for CharityML May 2017 - Present
DEPAUL UNIVERSITY
Masters of Science in Computer Science
Specialization: Data Science
Chicago, IL
January 2016   March 2018
GUJARAT TECHNOLOGICAL UNIVERSITY
Bachelor of Engineering in Computer Science
Gujarat, India
July 2011   June 2015
SKILLS
Programming Languages Python, R, Java, Scala, SAS, Android Data science skill sets
Hadoop, Apache Spark, MapReduce, Tableau, Pandas, NumPy, Nearest neighbors, Support vector machines, Na ve bayes, Neural Networks, Time series analysis, Random forest, Decision tree, Scikit learn, MatplotLib Database MySQL, MongoDB
Web Development HTML, CSS, JavaScript, JSP, Servlet PROFESSIONAL EXPERIENCE
GRAPE INFOTECH
Web Developer
Ahmedabad, GJ
June 2015   October 2015
  Back end development of websites using PHP and JavaScript.
  6 people were working in a team, where individual sections were to be integrated at the end of each project. PROJECTS
Data and Prediction Analysis on Lending club April 2017   May 2017
  For the Advanced Data analysis class, we took Kaggle Dataset and perform advanced analysis using R. I particularly performed Principal component analysis and K-means clustering algorithm. Techniques used: R, Principal component analysis, K-means clustering Used Car Analysis February 2017   March 2017
  Perform multiple regression on the Used car dataset from the Kaggle.com using SAS. We were 3 members in a team and due to a large dataset with approx. 350K+, we each chose 1000 observation randomly. Techniques used: SAS, transformation, outlier removal, multiple regression Mental Health Visualization Analysis
February 2017   March 2017
  Visual analysis of Mental health data set from Kaggle.com using Tableau and R. We were 3 members in a team and each member individually did analysis and we chose best graphs to present. Techniques used: Tableau and R
Item-Based Movie Filtering November 2016
  Movie dataset has number of movies with its user ratings using Python. I predict suggestions to a user depending on what movies he/she watched.
Techniques used: Python
RELATED COURSEWORK
  Foundations of Data Science   Data Analysis & Regression   Data Visualization
  Advanced Data Analysis   Object oriented Enterprise Computing   Database Technologies CERTIFICATIONS
  Certificate for Data Science and Machine Learning Hands On by Udemy
  Certification for Techniques and Concepts of Big Data by Lynda.com
  Certificate for Big Data 101 by Bigdata University