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Aspiring Data Scientist Ezhil Thaenraj, Websites, IT & Software
EDUCATION: University of California, San Diego | B.S. Data Science | Track: Machine Learning and Artificial Intelligence Halıcıoğlu Data Science Institute, UC San Diego California High School Coursework: Principles of Data Science , Programming and Basic Data Structures for Data Science , Theoretical Foundations of Data Science I , Calculus and Analytic Geometry for Science and Engineering , Linear Algebra, Statistical Methods , Exploratory Data Analysis and Inference SKILLS : Concepts: Data Structures, Classification, Regression, Machine Learning, Data Pipelining, Databases, Distributed Computing Languages: Java, Python, SQL, R, C#, Spark, Scala, HTML, CSS , Django Tools: Azure DataBricks, Azure SQL, Azure WebApps, Pandas, Numpy, Scikit-learn, MLLib, Librosa, RStudio, Microsoft Office PROFESSIONAL EXPERIENCE: Student Developer, STUDEV Aug. 20 – Dec 25· Part-Time · Performed extensive analysis of client’s data using Azure Databricks and R to provide insights · provided statistical and graphical analysis of sales data for multiple clients Web Developer, Keneland LLC Aug. 20 – Sept. 20 · Full-Time · Designed Keneland LLC's webpage using Django and hosted through Azure Web Apps and Django · Built a responsive site that dynamically handles presentation in desktop and mobile browsers through Azure Webapps · Created a sleek user interface with affordances to improve navigability and overall user experience Code Coach, The Coder School Jun. 18 – Jun. 19 · Instructed students from age 8-18 regarding how to code in a multitude of programming languages · Led group instruction sessions regarding hardware usage such as the Raspberry Pi and Arduino Uno · Managed front desk and greeted incoming customers as well as managed back end scheduling PROJECTS: Credit Risk Classifier: Used pyspark, pandas, numpy, matplotlib, sclearn and MLlib packages to classify whether or not a given record classifieds as a credit risk. Created a Machine Learning pipeline that accurately predicts this information using Logistic Regression on enormous datasets (> 10 million records) Link : https://github.com/pranavt2001/CreditRisk_LogisticRegression NYC Yellow Cab Project:: Took NYC Taxi data from the city archives and performed data analytics to collect insights regarding needless cab usage for Intra-Borough Travel and how the reduction cab usage in these cases can reduce ones carbon footprint. Link: https://github.com/pranavt2001/NYC-Taxi Movies MetaData Project: Took the Movies dataset from Kaggle and performed multiple data transformations to filter and produce movies that were most apt for children given their particular interests by genre. Link: https://github.com/pranavt2001/Kaggle-Movies-Metadata COVID-19 Project: Took COVID-19 data from covidtracking.org and performed multiple transformations to collect insights regarding the daily increases in cases per state, The testing rates of each state, and more. Took these individual insights and presented them in understandable visual representations. Went on to create widgets that automated filters for user ease. Link: https://github.co m/pranavt2001/COVID-19 MLB LSLR: Using R to perform Linear regression on a dataset of MLB salaries and other features that either categorize as indicators of performance or indicators of experience and performed single variable and multiple variable regressions to see if features of experience, features of performance, or a combination of both made the best model for predicting player salaries Link: https://github.com/pranavt2001/MLB_LSLR Certifications: Databricks Certified Associate Developer for Apache Spark 3.0: Issued Sept 2020 Databricks Certified Associate ML Practitioner for Apache Spark 2.4: Planned for Mar 2020
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R Programming Language
Full Stack Developer Sushant Sawant, Websites, IT & Software
Over all 5.5 years of experience in developer role. • Programming Language – Java, Scala, Erlang, R, SQL, C, C++, Python (Cpython, Ironpython), Nodejs, Golang. • Database – Oracle 2012, MYSQL, Cassandra, MongoDB, Apache Solr, Hadoop, Elasticsearch,Redis. • Big data processing – Apache Flink, Apache Spark, Apache Thrift, Apache Airflow, Kubeflow. • Queuing Technology- Apache Kafka, NSQ • BI tools: IBM Cognos, QlikSense, Tableau. • Any technology most welcomed. Also an language agnostic.
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