MLops Engineer, open source contributor and AWS Community Builder.Keen interest in the Cloud, building ML pipelines, Graph DB, MLOps and the all things AWS.
I'm a MLops Engineer from London. My love for data began in 2016 and I feel so privileged to be part of thiscommunity.
I love contributing to open source projects in my spare time and also experimenting with new techniques and tools.
🔭 I’m currently working on: mytechnical blogs
🌱 I’m currently skilling up on:
- AWS Developer Associate Certification
- Personal Project on Sagemaker (something Computer Vision related with Tensorflow
- Neo4j Data Science Certification
- Bayesian ML (pymc3 and hyperopt)
- Terraform and achieving the certification
- JavaScript (nodejs and re-learning D3js)
- Forecasting American Football Fever in AWS using Wikipedia Page Hits
- Detecting Fraud in Credit Card Transactions using AWS Fraud Detector
- Recommending movies using AWS Personalize
- Unit Testing SQL using tSQLt
- Examples of deploying and hosting a Machine Learning Model with FastAPI
- Using multiple AWS NLP services architecture for translating audio file
- Classifying food images into correct categories using AWS Rekognition
- Understanding AWS VPC terminology with practical examples
- Scheduling RDS instances with AWS EventBridge
- Running a Spark notebook in EMR
- Streaming Tweets using AWS Kinesis
- Spatial Analytics to understand impact of socio-economic factors on wellbeing in citizens across London
- Orchestrating ETL workflow using AWS Step Function
- D3js Visualisation submitted and shortlisted in the 360 Giving GrantNav Challenge
- Twitter Analytics for Global Health
- Tableau Visualisation looking at funding in the UK Grantmaking sector for the 360 Giving Challenge
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- AWS-ETL-Workflows
AWS-ETL-Workflows PublicExamples of architectures using a number of database, compute and etl services in AWS
- databricks_spark_certification
databricks_spark_certification PublicPrep for the databricks spark 3 certification
- probabilistic_graphical_models
probabilistic_graphical_models PublicImplementation Bayesian Networks using pomegranate, pgmpy and networkx
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