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Hi there 👋

Thank you for visiting my profile. I have been working with the technology over about 7 years and have expertise in multiple areas such as machine learning, data engineering and software engineering using python. I work on AWS and is familiar with building data pipelines and orchestration mechanisms suitable for either data analysis, or driving that for machine learning. I am improving my cloud capabilities, and like to apply them in cloud related architectures with DevOps, data engineering, and analytics domains.

🔭 Exploring and implementing data pipelines in AWS.

Meantime, I also do some contribution to help anyone. Below are some good references of my projects:

Data Engineering / Data Science in Python 🚀 :

  1. Crawler for google scholar to extract author information - https://github.com/bethgelab/google_scholar_crawler
  2. HPC monitoring application using Telegraf,Influx,Grafana (TIG) - https://github.com/bethgelab/slurm-monitoring-public
  3. Detect Traffic Signs - https://github.com/prakass1/detect-traffic-signs
  4. Detect Gestures (Also a dataset contribution) - https://github.com/prakass1/GestureRecognition
  5. Udacity Projects - AWS Data Engineering Nanodegree (Will be updated incrementally)
    -- EMR Computation: https://github.com/prakass1/aws-etl-emr
    -- Other Lessons: https://github.com/prakass1/DE-nano-degree
    -- Performing ETL using AWS: https://github.com/prakass1/sparkify-etl-aws
    -- ETL using cassandra: https://github.com/prakass1/udacity-sparkify-etl-cassandra
    -- ETL using python: https://github.com/prakass1/udacity-sparkify-etl.
    -- ETL orchestration with Airflow: https://github.com/prakass1/airflow-etl.
    -- The Final term project: https://github.com/prakass1/udacity-de-capstone.git
  6. My Master Thesis protoype tool for Medical Analytics - https://github.com/prakass1/InteractiveSimilarityExplorer
  7. Implementation of Rank Based Outlier Detection using kNN - https://github.com/prakass1/Rank_Based_Detection_Algorithm

Software Engineering in Python 🚀

  1. Flask-Restful template with an example of getting daily quotes - https://github.com/prakass1/Flask-Restful-Template
  2. A blogger application which can help to setup your own with already built-in components - https://github.com/prakass1/SimplisticBlogger
  3. Digit recognizer application - https://github.com/prakass1/digitrecognizer

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Subash Prakash's Projects

amazon-redshift-checklist icon amazon-redshift-checklist

This checklist aims to be an exhaustive list of all elements you should consider when using Amazon Redshift.

aws-etl-emr icon aws-etl-emr

ETL process using Amazon AWS, S3, and EMR for ETL processes

bingo_game icon bingo_game

A simple bingo game to play with friends over online

black icon black

The uncompromising Python code formatter

data-science-lit icon data-science-lit

All the Data Analysis exploration projects will be present here either as jupyter :notebook: or :snake: code.

detect-traffic-signs icon detect-traffic-signs

Recognizing Traffic signs from GTSRB dataset ||:red_circle:||:small_red_triangle:||:small_red_triangle_down:||

devops-resources icon devops-resources

DevOps resources - Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git, Kubernetes, Terraform, OpenStack, SQL, NoSQL, Azure, GCP

digitrecognizer icon digitrecognizer

Hand Written Web Application for Digit Recognition Using Tensorflow and Python

dlwpt-code icon dlwpt-code

Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.

ds-career-resources icon ds-career-resources

Compilation of resources and insights that helped me on my journey to data scientist

handson-ml2 icon handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

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