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Data Python

Chicago, Illinois, United States
November 19, 2018

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Namaswi Chandarana *** W Jackson Blvd Apt 508, Chicago, IL 60661 312-***-****

Linkedin Profile: EXPERIENCE

Data and Marketing Intern

Ragan Communications, Chicago, IL June 2018 - PRESENT

● Used basic NLP techniques to find duplicates in databases

● Analyzed and visualized time series data and assist in drawing conclusions on the information

● Created reports and presented findings and data to the team to improve strategies

● Used Microsoft Excel to create pivot tables and to work with advanced functions such as VLOOKUP

● Automated the update of data collected by Quickfill on SugarCRM

● Used Google Custom Search API to validate company detail entries

● Relevant Tools: Python(Jupyter Notebook, Spyder), SugarCRM, Plotly, Rest API, Google Custom Search API EDUCATION

University of Illinois at Chicago, IL

Master of Science in Computer Science, GPA: 4/4 Expected May 2019 Relevant Courses: Data Mining and Text Mining, Neural Networks, Visual Data Science, Visualization and Visual Analytics, Applied Artificial Intelligence, Computer Algorithms, Development of Mobile Apps, Creative Coding University of Mumbai, Mumbai, India

Bachelor of Engineering in Computer Engineering, GPA: 8.49/10 June 2017 Relevant Courses: Software Engineering, Algorithms and Program Structures, Database Management, Object Oriented Programming


Programming Languages : JAVA, Python (Pandas, Numpy, Scikit), R, PHP, C, Jess Databases :Oracle, MySQL, JSON, Hadoop

Web Technologies : Rest API, HTML5, CSS3, JavaScript, JSON, Bootstrap,WordPress Software Tools : Android Studio, Eclipse IDE, NetBeans, Unity, Maya Visualization Tools : D3.js, Shiny using R, Three.js Machine Learning Tools : Rstudio, Anaconda(Spyder, Jupyter Notebook), Microsoft Azure Machine learning Machine Learning Algorithms : Decision Trees, KNN, Linear/Logistic Regression, SVM, Random Forest, Neural Networks ACADEMIC PROJECTS

1) Computational fluid flow simulation dataset from the San Diego Supercomputing Center (Three.js and D3.js) 2) Handwritten Digit Classification using MNIST Data (Python, Numpy) 3) Time Series Prediction and Forecasting using Vector Auto Regression on Air Quality Dataset (Python,Numpy, Datatime, Matplotlib)

4) Data Visualization project on USA DEATHS 2012-2013 (D3.js) 5) Aspect-Based Sentiment Analysis on Restaurant and Laptop Reviews (Python, spacy, Numpy, Pandas, Sklearn) 6) Data Visualization project using USA Tornado dataset (R, Shiny, Plotly ) 7) Data Visualization project using USA Domestic Flights (R, Shiny, Plotly) 8) Zillow’s Home Value Prediction (Kaggle, Python, Numpy, Pandas, Sklearn, XGBoost) 9) Titanic Machine Learning Disaster (Kaggle, Python, Numpy, Pandas)

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