aakanksha n
Machine Learning Engineer at Snap Inc.
machine learning engineer snap inc .
master 's graduate university san francisco , studied data science focus applied machine learning . worked software engineer jp morgan chase two year completing b.tech computer science nit calicut , india . enjoy machine learning , competitive coding , web development .
Snap Inc.
https://www.linkedin.com/company/snap-inc-co
Building recommendation systems for Ad ranking
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Machine Learning Engineer
AbbVie
https://www.linkedin.com/company/abbvie
Irvine, California, United States
https://media-exp1.licdn.com/dms/image/C4E0BAQEDI_1b9ZuklA/company-logo_100_100/0/1625088304598?e=1655942400&v=beta&t=zEN4S8OFxfFRJAN2LdGueiQ1Lbt69bZQXzzWt3DU9js
Data Scientist
Zyper
https://www.linkedin.com/company/zyper.
Zyper (YCombinator '18) helps brands connect with their fans to drive engagement, insights, and sales. 

My contributions:
• Machine Learning Modeling: Developed and deployed a Deep Learning (PyTorch) model to identify image style, used for sourcing candidate profiles.
• Data visualization and Insights: Automated community insights extraction based on Sendbird group chats and user-generated content for the account management team to provide weekly updates to clients. 
• Churn Analysis: Defined user cohorts and performed a churn analysis based on engagement on user-generated content and user analytics data obtained from Mixpanel.
• A/B Testing: Set up an A/B test (determined key performance and guardrail metrics, design and nuisance factors, experimental conditions) to optimize price points for a product.
San Francisco Bay Area
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Data Science Intern
JPMorgan Chase & Co.
https://www.linkedin.com/company/jpmorganchase
• Developed interactive, user-friendly, ADA (Americans with Disabilities Act) compliant and responsive web interfaces & widgets for the Chase Online website and app used by over 15 million customers.
• Implemented object-oriented JavaScript, React, SASS/CSS for frontend and Java Spring for backend in an Agile software development environment.
• Maintained 100% unit test coverage with Sinon, Chai and Mocha.
• Mentored new employees on object-oriented JavaScript programming.
Bengaluru Area, India
https://media-exp1.licdn.com/dms/image/C510BAQF_zIelQWSBvw/company-logo_100_100/0/1519856321426?e=1655942400&v=beta&t=SIjKhLcttPF3Wq3SLqiyTobH0p4ZOzMILpjD6qcrmac
Software Engineer
JPMorgan Chase & Co.
https://www.linkedin.com/company/jpmorganchase
• Created dynamic reports on Oracle Automatic Workload Repository to track performance and identify abnormal data using JasperReports, Java Server Pages (JSP) and servlets.
Mumbai Area, India
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Summer Intern
Master of Science - MS
Courses Taken: 
Machine Learning, EDA and Data visualization, Time Series Analysis, Distributed Computing, Relational Databases, Data Acquisition, Case studies in Data Science, Data Ethics, Product Analytics, A/B Testing, Deep Learning, Reinforcement Learning
Data Science
https://media-exp1.licdn.com/dms/image/C4D0BAQHoTRX0GkGHuw/company-logo_100_100/0/1519856036530?e=1655942400&v=beta&t=mh1WJXl2-IYU6nLlJLw8afmnU2I2ThEPL4hGjmf2KQw
University of San Francisco
https://www.linkedin.com/school/university-of-san-francisco/
B.Tech
Selected coursework:
Data Mining, Pattern Recognition, Data Structures, Design and Analysis of Algorithms, Discrete Structures, Computer Organization, Computer Security, DBMS, Data Mining, Image Processing, Number Theory and Cryptography, Operating Systems
Computer Science and Engineering
https://media-exp1.licdn.com/dms/image/C4E0BAQGV9kVeWPEERA/company-logo_100_100/0/1519900513672?e=1655942400&v=beta&t=SqmBMQznQRGlb8jn7v2hOggJXp05bSNheIYKPu_pFfY
National Institute of Technology Calicut
https://www.linkedin.com/school/national-institute-of-technology-calicut/
• Predicted bounding boxes around wheat heads, given an image of crops using a Faster RCNN deep learning model with a ResNet-152 backbone in PyTorch.
• Achieved a mean precision value of 0.7
Object Detection
https://github.com/aakanksha-ns/wheat-detection
•  This app allows users to improve their media literacy by taking a critical eye towards what news items are forwarded to them in a quick, informative dashboard. 
•  Automates cross-checking for quick verification and provide a more complex approach of machine learning as an option, so they can understand why and how to verify digital information.
Factnews - Digital media literacy and fact-checking web application
http://factnews.io/
Designed and developed an online bookstore where a user can register, login, add books to cart, and checkout. 
Used Heroku Postgres, SQLAlchemy, and Flask for back-end; React and Redux for front-end.
Online Bookstore
https://book-store-c8fb5.firebaseapp.com/
• Built a deep learning model to predict the user rating (in the range 1-5) of a product, given its review comments from the user.
• Used an LSTM model in Pytorch and achieved a Root mean squared error (RMSE) of 0.79.
Item Rating Prediction
https://towardsdatascience.com/multiclass-text-classification-using-lstm-in-pytorch-eac56baed8df
• Determined which device-algorithm combination is best at recognizing 18 types of human activities (like jogging, running, eating etc.) using sensor readings from phone and smartwatch.
• Used Apache PySpark for distributed preprocessing of the time-series data to extract about 50 handcrafted features per observation.
• Compared various Spark ML, H2O, AutoML models and found XGBoost on H2O to be the best model in identifying the activities. Also compared the best algorithm's time efficiency in various AWS EMR cluster settings.
• Found that using phone and watch data is better than using phone only and watch only.
Human Activity Recognition
https://github.com/aakanksha-ns/Human_Activity_Recognition
• Built a custom dataset by web scraping using the BeautifulSoup library.
• Developed a deep learning model using transfer learning from ULMFiT architecture and finetuning it to generate lyrics given a phrase as prompt.
Lyrics Generator (Web scraping, Deep Learning, NLP)
https://taylor-swift-lyrics-generator.firebaseapp.com/
• Compared various regression algorithms like Naive Bayes Regressor, Random Forests, Linear Regression etc. using scikit-learn
• Fine tuned the best regressor (Random Forests) using randomized search.
• Predicted box office revenue with an R square score of 0.85
Box Office Revenue Prediction
https://github.com/ShreejayaB/TMDB-Box-Office-Predictions
• Built an end-to-end web application to identify the type of a flower given its image 
• Used fast-ai library to train the model using transfer learning from ResNet-34. The model could classify 5 categories with an accuracy of 94.4%. 
• Created an API using Flask and deployed it on Render.com. Built a React-based frontend and deployed it on Firebase.com
Flower Classification Web App (Deep Learning, Image Classification)
https://flower-classifier-dad75.firebaseapp.com/
• Generated a custom dataset using Google images. 
• Trained a model to identify the genre (horror, romance, superhero) of a movie by looking at its poster with an accuracy of 80%. 
• Performed various experiments on the model to improve accuracy and made observations about them.
Movie Genre Identifier
https://medium.com/@aakanksha.ns/building-a-movie-genre-classifier-using-a-dataset-created-using-google-images-4752f75a1d79
• Built an Android application that detects the genre of a song given as input. 
• Extracted Mel-Frequency Cepstrum Coefficients (MFCC) from over 1000 songs and trained a three-layer neural network model to perform classification based on genre.
• Compared performances of various Machine Learning algorithms such as SVM, Random Forests, Neural Networks, etc.
• Identified Jazz, Classical, Metal and Pop songs with an accuracy of 80%
Music Genre Detector (Audio Processing, MFCC extraction)
https://github.com/AkshayeAnithaPradeep/Piper
• Developed a toy operating system on a simulated machine with all basic functionalities: running programs, creation/deletion of files, interrupts, etc.
• Implemented multiprogramming by invoking timer interrupts
Experimental Operating System
http://exposnitc.github.io/
Education
Paathshala
Co-founded an initiative called Paathshala, a charitable organization to provide school-like education to underprivileged children in and around our college campus. Over the course of 3 years, we taught more than 20 children how to read, write and perform basic calculations.
Co-Founder
Coursera
www.coursera.org
QM4NJAU4CNW2
Introduction to TensorFlow
https://www.coursera.org/account/accomplishments/certificate/QM4NJAU4CNW2
Correlation One
www.credential.net
19865327
Data Science For All Women Summit San Francisco
https://www.credential.net/13b350b7-a6e1-4623-aeea-c519ce8b870b
Workera
app.workera.ai
TZLFYQCV
Deep Learning Engineer
https://app.workera.ai/public/candidate/certificate?code=TZLFYQCV
University of San Francisco
Fundamentals of Deep Learning Using Pytorch
Coursera
www.coursera.org
Z3THU27U55BP
Deep Learning Specialization
https://www.coursera.org/account/accomplishments/specialization/Z3THU27U55BP
Coursera
www.coursera.org
4XUBPWKBL2JE
Machine Learning
https://www.coursera.org/account/accomplishments/certificate/4XUBPWKBL2JE
https://www.linkedin.com/in/yang-zhang-4563a2104
Sunnyvale, CA
Yang Zhang
Machine Learning/Deep Learning Research Engineer
https://www.linkedin.com/in/devin-lu-00867390
Stanford, CA
Devin Lu
Software Engineer at Snap Inc.
https://www.linkedin.com/in/ganeshparameswaran
Sunnyvale, CA
Ganesh Parameswaran
Senior Software Engineer, Machine Learning
https://www.linkedin.com/in/phamkhang
Palo Alto, CA
Khang Pham
Software Engineer at Snap Inc
https://www.linkedin.com/in/roshanr1
New York City Metropolitan Area
Roshan Ramkeesoon
Machine Learning Engineer at Snap Inc.
https://www.linkedin.com/in/sahil2441
San Francisco Bay Area
Sahil Jain
Software Engineer @Snap, previously @Google
https://www.linkedin.com/in/chunhui-zhu-51730843
San Francisco Bay Area
Chunhui Zhu
Engineering Manager @ Snap Inc | Hiring ML and Backend/Infra Engineers
https://www.linkedin.com/in/jiao-liu-scu
Santa Clara, CA
Jiao Liu
Graduate student of Santa Clara University | vGHC 2021 | Software Engineer |  MSIS
https://www.linkedin.com/in/arman-pathan
Greater Seattle Area
Arman Pathan
Software Engineer 2
https://www.linkedin.com/in/nandita-singh-09
Milpitas, CA
Nandita Singh
Data Science Engineer at Abbott
https://www.linkedin.com/in/xin-guo-nowhere
Greater Seattle Area
Xin Guo
Engineering Manager at Snap Inc.
https://de.linkedin.com/in/11rashidar
Berlin Metropolitan Area
Rashid Abdul Rahiman
Junior Technical Engineer at SAP SE | COE EMEA Analytics
https://www.linkedin.com/in/namrata-kasar-035b79162
San Francisco Bay Area
Namrata Kasar
Software Engineer 3 at eBay
https://www.linkedin.com/in/iackerman
United States
Ian Ackerman
Building the Smart Platform to Deliver Relevant News
https://www.linkedin.com/in/nehabindle
Sunnyvale, CA
Neha Bindle
Software Developer Engineer at Alexa Music
https://www.linkedin.com/in/ayushpareek
San Francisco Bay Area
Ayush Pareek
Machine Learning Engineer at Apple |  Data Scientist Intern at Microsoft | Research Grad at CMU, Yale
https://www.linkedin.com/in/bharatsimhareddyrs
Dallas, TX
Bharat Simha Reddy Rikkala Sudhakera
Member of Technical Staff 3, VMware | MS CS, UTD
https://www.linkedin.com/in/maunil-vyas-456919106
San Francisco Bay Area
Maunil Vyas
Machine Learning Engineer at Amazon
Richard Hanson
      
          



            
              
        
              
  

    
        Aakanksha has worked on various data science projects over the last year, ranging from data exploration and data analytics tasks to deep learning computer vision models and entity extraction nlp models that help Zyper better understand communities and provide tangible benefits to internal stakeholders and our users.
In each case she developed clear goals and success criteria, prototyped approaches and rigorously validated her assumptions before delivering production-ready tools and pipelines.
She has found creative solutions to solve immediate business needS, whilst learning new technologies to deliver results in short iteration cycles, continuously factoring in feedback from users.
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Friday book recommendation #11:I am a big fan of Cal Newport’s work. It’s amazing how he notices relevant issues, researches and thinks deeply…
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Happens with you!?
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Avanade United States  values are motivating, diverse and inclusive culture creates an amazing environment to be innovative/productive for everyone…
F1 visa Job Seekers
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University of San Francisco (USF)
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USF MSDS Cohort 8
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USF MS in Data Science Alumni
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