ac4cqw@r.postjobfree.com

Sagar Vadher

LinkedIn

626-***-**** Los Angeles, CA GitHub

EDUCATION

Master’s in computer science California State University Los Angeles, Los Angeles, CA. Sep 2015 – Dec 2017 Bachelor’s in computer engineering Gujarat Technological University, Ahmedabad, India. Aug 2009 – Jun 2013 EXPERIENCE

Lereta, Covina CA Web Developer Intern Jul 2016 – Sep 2016

• Collaborated with the developers to implement a robust and scalable web application and performed cross browser testing.

• Used technologies like AngularJS, HTML5 and CSS3 for designing and used MY SQL for backend database management. Eidolon Cyber Studio, Ahmedabad India Web Developer Intern Jul 2013 – Jun 2014

• Used web technologies such as HTML, CSS3, JavaScript, jQuery, XHTML and twitter bootstrap to develop responsive web applications.

• Effectively used various object-oriented program concepts while development of the web applications. SKILL SET

Data Science Tools: Pandas, Scikit-learn, Matplotlib, Numpy, Scipy, PyMC3 – Bayesian statistics, Plot.ly, NLTK, Kibana, Hadoop (currently learning)

Programing Languages: Java, Python, JavaScript

Web Technologies: Node JS, Angular JS, Amazon Web Services, Servlets, jQuery, HTML5, CSS3, JSP Version Control: Github, Jira

Databases: MySQL, MS SQL. MongoDB, PostgreSQL

PROJECTS

TOXIC COMMENTS CLASSIFICATION Fall 2017

• Built a classifier from Dataset contained 100,000 random comments from internet which were divided among toxic and non – toxic comments into further 5 sub-categories.

• Used Spacy, gensim word2vec, LDA, t-sne, Plotly for analysis. Used tf-idf Multiclass classification for prediction. AIRBNB ANALYSIS Fall 2017

• Built a ML model using Ridge and Lasso regression to predict if the user is getting a good deal in Los Angeles area.

• Used 2017 Airbnb data from its website along with SVM and Kernel PCA for reducing dimensionality. E-SPORTS TRACKER Summer 2017

• Built an Android application for live scores of e-sports using SportsRadar REST API using Firebase Job Dispatcher and Job Scheduler.

• Used Google card View, splash screen and Async task loader for UI. TWITTER GENDER CLASSIFICATION Spring 2017

• Developed a Categorical ML predictor to predict the gender of the twitter users based on their tweets with text mining.

• Used Multinomial Naïve Bayes along with TFIDF, Gaussian NB, Random Forest Classifier, Voting Classifier and AdaBoost. Used ROC curve to get a refined predictor.

SPOTIFY MUSIC SEARCH APP Spring 2017

• Built a web application using SPA - Node JS NPM module and Angular JS and REST services on Spotify API.

• User can enter the find artist’s album and songs details. Express was used for data routing, and MVC. IMDB MOVIE RATING PREDICTION Fall 2016

• Used Linear regression, cross-validations, PCA to build an estimator model.

• For a given actor and director and their genre, the system would predict an IMDB score. YELP ANALYSIS Summer 2016

• The yelp reviews Json data was stored using MongoDB and ElasticSearch. Kibana was for Exploratory Data Analysis and Gradle was used as a build tool.

• Used Amazon Web Service for displaying application on the web. STARBUCKS LOCATOR Spring 2016

• Developed J2EE MVC application that have functionality to locate Starbucks coffee shop by city, geographical coordinates. Used JavaScript, HTML5, CSS and Bootstrap for UI.

• The Starbucks coffee data was stored with the help of MySQL database.

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