Maneesh Gupta Email & Phone Number

Los Angeles, Ca, Us

San Francisco, California, Us

San Francisco, California, Us

San Francisco, California, Us

San Francisco, California, Us

San Francisco, Ca, Us

San Francisco, California, Us

Account Churn PredictionCall Volume ForecastingLead Conversion Modeling

Boulder, Colorado, Us

Assisted in teaching the Applied Natural Language Processing course at gU. This is an 8 week course that equips graduate students with the skills to solve real world NLP problems. -Taught core NLP concepts to students-Served as mentor for capstone projects-Helped students on the floor during lab-Reviewed current student code and graded capstone projectsCurriculum Overview:Week 1 - NLP Fundamentals, Regular Expressions, Segmentation/Tokenization/StemmingWeek 2 - Language Modeling, Text Encoding, Edit DistanceWeek 3 - Spell correction, Word Tagging, Named Entity RecognitionWeek 4 - Chatbots, Information RetrievalWeek 5 - Text Classification, Bernoulli Naïve Bayes, Multinomial Naïve BayesWeek 6 - Topic Modeling, Non-negative matrix factorization, Latent Dirichlet allocationWeek 7 - Word2Vec, Doc2Vec, Week 8 - Final ProjectPython Libraries: Gensim, nltk, textblob, sense2vec, ftfy,

Boulder, Colorado, Us

A 3 month immersive data science program culminating in a 2 week capstone project.Curriculum Overview:Week 1 – Exploratory Data Analysis & Software Engineering: (OOP, SQL, Pandas, data viz)Week 2 - Statistics & Probability: (Bayes, Hyp. Testing, A/B Testing, etc.)Week 3 - Regression: (Regularization, Classification, Gradient Descent, etc.)Week 4 - Supervised Machine Learning: (Decision Trees, SVM, Random Forests, KNN, etc.)Week 5 - Special Topics: (Clustering, Topic Modeling (NMF, LDA), NLP, Web Scraping)Week 6 - Unsupervised Learning: (Network Analysis, Matrix Factorization, and Time Series)Week 7 - Data Engineering: (AWS, S3, EC2, EBS, Hadoop, Hive, Spark, MapReduce, etc,)Week 8 - Case Studies: (Fraud Detection, Recommendation Systems, User Retention, etc.)Weeks 9-12 - Capstone Project (TweetSafe)Python Libraries:Gensim, Scikit-learn, PySpark, FlaskBig Data Tools:Spark, Amazon Web Services, PostgreSQL, mongoDB

Pasadena, Ca, Us

Worked with MIRO team scientists to determine the cause of the instrument calibration error. Independently collected and analyzed 10 years of data from a SQL database. Implemented a new model that reduced the calibration error to less than 1%. -Created a pipeline that analyzed 10 years of data using a custom peak detection algorithm-Presented weekly reports to MIRO team scientists-Wrote a script to automate cleaning and analysis of training data

Lexington, Ma, Us

Spent a summer fabricating and testing microfluidic devices as a cheap alternative for DNA sequencing. These devices used pyrosequencing to sequence a DNA sample contained inside the microfluidic device. -Designed new experimental setup for parallel testing of devices-Determined optimal conditions for binding silicon chips to PDMS-Doubled production of microfluidic chips

Master Of Engineering (M.Eng.), Mechanical Engineering

Bachelor Of Science, Applied Engineering Physics

Education record