A graduate student, and current SAP Cloud Engineer intern with 3 years of experience developing and scaling machine learning solutions to improve customer experience.
Created a service-oriented REST architecture based marketplace web app with CI/CD, load testing and dashboarding. Implemented the Infrastructure-as-a-Code (IaaC) paradigm and scaled the application to 5000 concurrent users and 2800 requests/second using simulated load testing via Gatling.
Experimented to utilise a novel Convolutional LSTM model to extract spatio-temporal features to predict crime hotspots over Vancouver city with 82% recall and 71% precision. Worked on developing a data collection api to extend model training for multiple cities and predit crime-wise hotspots.
Collaborated in a team to use Spark, AWS Lambda, S3 and Glue to implement an ETL pipeline to scrape and process civil aviation accident and incident records on a weekly basis and AWS Quicksight for dashboarding. Developed an unsupervised system using K-Means clustering algorithm to determine the possible features leading to fatalities/injuries in an accident.
Emof_ai is a web API which takes a sample video as an input, detects all the faces in each frame of the video and performs classfication. It classifies the emotion of the face into 1 of 8 emotions viz anger, disgust, fear, happy, sad, surprise, neutral and none(this is when there are no faces detected in the frame at all and hence none means no emotion detected in the frame at all). It also classifies the gender of the person. In addition to that, it also classifies the age group of the person into 1 of 4 age groups viz adult, child, old and youth.
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I got to learn how to employ MySQL to solve advanced business problems like traffic sources, website performances, channel portfolio management, seasonality, product and user analysis
I got to learn the basics of AWS and how to deploy CI/CD pipelines as well as serverless development on AWS, using tools like Lambda, API Gateway.
I completed 5 courses included in this specialization pertaining to Neural Networks, Convolutional Neural Networks and Sequence Models. Furthermore I also worked on several mini projects such as music generation and object detection.
This was the first course I took to learn concepts of Machine Learning. I learnt various concepts like Loss algorithm, Linear and Logistic Regression, Support Vector Machines, Random Forests. Furthermore, I also learnt the theory of Neural Networks
I learnt how to use PySpark client api to leverage the power of Apache Spark and solve big data problems. I learnt how to use Spark 2.0 DataFrame API as well as use the Spark Mllib library to train machine learning models.
This course taught me the mechanism behind Big Data. I learnt what is Hadoop and YARN, in addition to Apache Spark
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Checkout my interview at R3plica where I share how I started my professional career in AI, current breakthroughs in AI which excite me and various domains I wish to get AI implemented in.